# SynapCores

> SynapCores is a self-hosted, AI-native database in a single binary: SQL plus vector
> search, a graph engine, in-database AutoML, inline LLM functions (EMBED, GENERATE),
> and durable in-database agents (CREATE AGENT). MySQL-compatible. The Community
> Edition is free for Linux, macOS, and Docker.

## Key pages
- [Product](https://synapcores.com/product): what SynapCores is and who it is for
- [AI-native SQL reference](https://synapcores.com/sqlv2): EMBED, GENERATE, vector, graph, AutoML, CREATE AGENT
- [Developers & REST API](https://synapcores.com/developers): quickstart and SDKs (Node, Python, PHP, Go, Java)
- [Download — free Community Edition](https://synapcores.com/download)
- [Recipes index](https://synapcores.com/recipes): 221 runnable, certified recipes

## Recipes (221)
Each recipe is a runnable SQL or Cypher walkthrough with copy-paste code, verified
end-to-end on SynapCores. Grouped by category.

### advanced-patterns
- [Semantic Document Search](https://synapcores.com/recipes/112_semantic_document_search): Build intelligent document search using text embeddings for meaning-based retrieval
- [Audio Transcription and Analysis](https://synapcores.com/recipes/113_audio_transcription_analysis): Transcribe audio content and analyze transcripts with AI functions
- [Video Content Intelligence](https://synapcores.com/recipes/114_video_content_intelligence): Extract metadata, scenes, and insights from video content using AI functions
- [Multimodal Content Search](https://synapcores.com/recipes/115_multimodal_content_search): Search across images, videos, audio, and documents using unified vector search
- [Content Recommendation Engine](https://synapcores.com/recipes/116_content_recommendation_engine): Build a recommendation system using vector similarity and user behavior
- [Media Workflow Automation](https://synapcores.com/recipes/117_media_workflow_automation): Create automated media processing pipelines with status tracking and notifications
- [Media Analytics Dashboard](https://synapcores.com/recipes/118_media_analytics_dashboard): Build comprehensive analytics for media usage, engagement, and performance
- [Media Compliance and Audit](https://synapcores.com/recipes/119_media_compliance_audit): Track media compliance, retention policies, and audit trails for governance
- [Cross-Platform Media Sync](https://synapcores.com/recipes/120_cross_platform_media_sync): Synchronize media assets across multiple platforms and track sync status
- [Performance Marketing: True ROAS and Customer LTV Across Facebook, TikTok and Google](https://synapcores.com/recipes/121_performance_marketing_roas_ltv): Join platform ad spend to your own clickstream, attribute conversions last-touch, and rank campaigns by 90-day LTV:CAC instead of day-0 ROAS — the ranking flips, and the recipe shows you why.

### agents
- [A Self-Improving Agent (learn from feedback)](https://synapcores.com/recipes/agents/a-self-improving-agent-learn-from-feedback): Build an AI agent that learns from thumbs-up/down feedback — train a model on past interactions to predict whether a draft reply will satisfy the user, all in one SQL database. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Prove an AI Agent's Decision Was Never Altered (Clinical Decision Support)](https://synapcores.com/recipes/agents/agent-decision-traceability-clinical-decision-support): Run a deterioration-watch agent that can read the chart but never write to it, then keep a hash-chained, append-only record of every recommendation it made — the traceability a clinical safety review actually asks for.
- [Prove an AI Agent's Decision Was Never Altered (Loan Underwriting)](https://synapcores.com/recipes/agents/agent-decision-traceability-loan-underwriting): Give a loan-review agent a hard governance envelope, then hand a regulator a tamper-evident, hash-chained record of every decision it made — all in SQL, inside one database.
- [Agentic DevOps Incident Triage](https://synapcores.com/recipes/agents/agentic-devops-incident-triage): An incident-triage agent that correlates the alert with recent deploys, runbooks, and customer impact — producing a structured 'here's what I see / suspected cause / recommended action' in one SQL call.
- [Agentic FinServ Compliance Reviewer](https://synapcores.com/recipes/agents/agentic-finserv-compliance-reviewer): A compliance-reviewer agent that walks the transaction table, consults KYC docs and regulations by meaning, surfaces hits with citations, and drafts an SAR-style write-up — all in SQL via AGENT_RUN.
- [Agentic Healthcare Clinical Q&A](https://synapcores.com/recipes/agents/agentic-healthcare-clinical-qa): A clinical-assistant agent that grounds answers in the patient's chart AND the relevant guideline — never just one or the other. Built on a single SQL session with AGENT_RUN.
- [Agentic HR Employee Q&A](https://synapcores.com/recipes/agents/agentic-hr-employee-qa): An HR-assistant agent that combines the employee's specific row (country, tenure, role band) with the right policy doc to answer correctly — not a generic RAG-only bot that hallucinates country-specific rules.
- [Agentic Insurance Claims Triage](https://synapcores.com/recipes/agents/agentic-insurance-claims-triage): Stand up an in-database claims-adjuster agent that retrieves policy clauses by meaning, scans prior-claim history for fraud signals, and recommends an action — all in a single SQL session via AGENT_RUN.
- [Agentic Legal — Contract Clause Review](https://synapcores.com/recipes/agents/agentic-legal-contract-review): A contract-reviewer agent that diffs an inbound MSA against your standard playbook AND your recent negotiated precedents — surfacing deviations with the closest prior deal as a reference.
- [Agentic Logistics — Shipment Exception](https://synapcores.com/recipes/agents/agentic-logistics-shipment-exception): A shipment-exception agent that joins the late shipment with the customer's SLA tolerance and recalls similar past exceptions, then drafts both the customer notice and the carrier dispatch — in one SQL call.
- [Agentic Retail Returns Triage](https://synapcores.com/recipes/agents/agentic-retail-returns-triage): A returns-processing agent that reads the order, checks return-policy by meaning, scans for abuse patterns in prior returns, checks live inventory for swap availability, and recommends a specific action — all in SQL via AGENT_RUN.
- [Agentic SaaS Support — Tier-1 Auto-Resolution](https://synapcores.com/recipes/agents/agentic-saas-support-tier1): A tier-1 support agent that reads the customer's actual account state AND the help docs in one call, then either resolves the ticket or escalates with full context — not a RAG-only chatbot.
- [Agentic Sales Account Research](https://synapcores.com/recipes/agents/agentic-sales-account-research): An account-research agent that pulls the CRM record, finds similar past wins by meaning, and outputs a one-page briefing before the sales call — all in SQL via AGENT_RUN.
- [Build a Customer-Support Agent on One Database](https://synapcores.com/recipes/agents/build-a-customer-support-agent-on-one-database): Build a complete AI customer-support agent on one database — semantic ticket memory, RAG over your help docs, intent routing, priority scoring, and a customer graph, no five-service stack. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Build a Personal Assistant Agent (memory + tools + RAG)](https://synapcores.com/recipes/agents/build-a-personal-assistant-agent): Build a personal AI assistant on one database — long-term memory of preferences, semantic tool routing, RAG over your notes, and grounded replies. No five-service stack. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Build a Research / Knowledge Agent (RAG + KG)](https://synapcores.com/recipes/agents/build-a-research-knowledge-agent-rag-plus-kg): Build an AI research agent that reads documents, builds a knowledge graph, answers multi-hop questions with citations, and synthesizes a briefing — RAG plus a knowledge graph in one database. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Build a Triage / Routing Agent](https://synapcores.com/recipes/agents/build-a-triage-routing-agent): Build an AI triage agent that classifies every incoming request by meaning, scores its urgency with AutoML, and routes it to the right queue or human — all on one database. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Build an Agent Knowledge Graph from Text](https://synapcores.com/recipes/agents/build-an-agent-knowledge-graph-from-text): Turn unstructured text into a queryable knowledge graph an AI agent can reason over — extract entities and relationships with GENERATE, store them as a Cypher graph, all in one database. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Build an AI SDR / Outbound Agent](https://synapcores.com/recipes/agents/build-an-ai-sdr-outbound-agent): Build an AI SDR agent on one database — score leads with AutoML, match them to case studies by meaning, map the buying committee as a graph, and draft personalized outreach with GENERATE. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [The Backend for a Coding Agent: Memory + Code Search + Impact Graph + Audit](https://synapcores.com/recipes/agents/coding-agent-backend-memory-rag-graph-audit): Stand up everything a coding agent needs — project memory, semantic code search, a code-dependency impact graph, and a tamper-evident decision log — on ONE self-hosted database it queries over MCP or SQL. No stitching four datastores; your code never leaves your box.
- [Conversation Memory + Rolling Summary for a Chatbot](https://synapcores.com/recipes/agents/conversation-memory-and-rolling-summary-for-a-chatbot): Store a chatbot's full conversation history and keep a rolling summary so it never blows the context window — turn buffer, semantic recall, and auto-summary in one SQL database. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Conversation Memory + Structured Facts for a Chatbot](https://synapcores.com/recipes/agents/conversation-memory-structured-facts-for-a-chatbot): The next-step variant of the rolling-summary recipe — replace the single prose summary with a typed chat_facts table (category, key, value, confidence, updated_at). Higher recall, surgical updates, no contradiction accumulation.
- [Customer Support Inbox: Sentiment Triage & Routing](https://synapcores.com/recipes/agents/customer-support-inbox-sentiment-triage): Classify every inbound support message with SENTIMENT() and auto-route it to the right team, owner, and priority — no external NLP service.
- [Episodic + Semantic Memory for an Agent](https://synapcores.com/recipes/agents/episodic-and-semantic-memory-for-an-agent): Give an AI agent two memory types — episodic (what happened, when) and semantic (durable facts) — in one SQL store, and recall across both by meaning. Framework-agnostic: Claude Code, OpenClaw, LangChain, or a voice agent.
- [Give Any AI Agent Long-Term Memory (in SQL)](https://synapcores.com/recipes/agents/give-any-agent-long-term-memory): Add persistent, semantic long-term memory to any AI agent — store and recall memories by meaning with vector embeddings in plain SQL. Framework-agnostic: works with Claude Code, OpenClaw, LangChain, or a custom or voice agent.
- [GraphRAG: Multi-hop Answers for an Agent](https://synapcores.com/recipes/agents/graphrag-multi-hop-answers-for-an-agent): Give an AI agent multi-hop reasoning — combine semantic retrieval with a knowledge graph so it can answer questions that need several connected facts, not just one passage. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Intent Classification for an Agent](https://synapcores.com/recipes/agents/intent-classification-for-an-agent): Classify what a user wants — billing, support, sales, cancel — so your AI agent routes the conversation correctly, using vector nearest-example matching in plain SQL. No training job, works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Shared Memory for Multi-Agent Systems (Blackboard Pattern)](https://synapcores.com/recipes/agents/multi-agent-shared-memory-blackboard): Let multiple AI agents collaborate through one shared memory — a blackboard where each agent posts findings and reads what the others know, by meaning, in plain SQL. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [RAG: Ground Any Agent's Answers in Your Data](https://synapcores.com/recipes/agents/rag-ground-any-agent-answers-in-your-data): Build retrieval-augmented generation for any AI agent in one database — embed your docs, retrieve the most relevant chunks by meaning, and generate a grounded answer in plain SQL. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [RAG with Citations (grounded answers that cite sources)](https://synapcores.com/recipes/agents/rag-with-citations): Make an AI agent cite its sources — retrieve passages, generate an answer, and attach the source documents it used, all in one SQL database. Auditable RAG that works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Recall Agent Memory by Meaning + Recency](https://synapcores.com/recipes/agents/recall-agent-memory-by-meaning-and-recency): Make an AI agent recall the right memories by blending semantic relevance with recency — fresh, on-point context in one SQL query, no separate vector store or cache. Works with Claude Code, OpenClaw, LangChain, or a voice agent.
- [Self-Checking / Grounded Generation (validate the answer)](https://synapcores.com/recipes/agents/self-checking-grounded-generation): Stop your AI agent from hallucinating — generate an answer, then have the agent verify it against your source data before returning it, all in one SQL database. Self-checking RAG for Claude Code, OpenClaw, LangChain, or a voice agent.
- [Semantic Deduplication of Agent Memories](https://synapcores.com/recipes/agents/semantic-deduplication-of-agent-memories): Stop your AI agent from storing the same fact ten times — detect and merge near-duplicate memories by meaning with vector similarity in plain SQL. Keeps agent memory clean for Claude Code, OpenClaw, LangChain, or a voice agent.
- [Semantic Tool Routing (function-calling without a framework)](https://synapcores.com/recipes/agents/semantic-tool-routing): Route an AI agent's request to the right tool by meaning — semantic function-calling with vector embeddings in plain SQL, no framework, no brittle keyword rules. Works with Claude Code, OpenClaw, LangChain, or a voice agent.

### aml
- [Trace Where the Money Went — Fund-Flow Tracing from a Flagged Account](https://synapcores.com/recipes/aml/01_fund_flow_tracing): Follow funds downstream from a flagged account through mule and shell layers in a single graph query — the traversal a JOIN-heavy SQL query fights you on.
- [Detect Structuring — Sub-Threshold Deposit Clustering in SQL](https://synapcores.com/recipes/aml/02_structuring_detection): Catch customers who break a large amount into many sub-$10k deposits to dodge the CTR threshold — a single GROUP BY … HAVING query over your transactions.
- [Retrieve the Most Similar Prior SARs by Narrative Meaning](https://synapcores.com/recipes/aml/03_sar_narrative_dedup): Ground a new SAR in your own filing history — find the most semantically similar past suspicious-activity reports so analysts reuse proven narrative language and stay consistent for the examiner.
- [An Examiner-Ready, Tamper-Evident SAR Decision Ledger](https://synapcores.com/recipes/aml/04_immutable_sar_ledger): Record every alert disposition and SAR decision — analyst, rationale, filing reference — in a cryptographically hash-chained, encrypted-at-rest immutable table your FFIEC/OCC/FinCEN examiner can verify in one query.

### anomaly-detection
- [Credit Card Fraud Detection (AutoML)](https://synapcores.com/recipes/anomaly-detection/001_credit_card_fraud_automl): Train a binary classifier on labelled transactions, deploy it, and score new transactions in real time — the BFSI ground-truth pattern for card-not-present fraud.
- [SaaS Account Takeover Detection (AutoML)](https://synapcores.com/recipes/anomaly-detection/002_saas_account_takeover_automl): Train a binary classifier on logins to catch credential-stuffing + session hijack attempts in real time — the SaaS security ground-truth pattern for account takeover (ATO).
- [Insurance Claim Fraud Auto-Flag (AutoML)](https://synapcores.com/recipes/anomaly-detection/003_insurance_claim_fraud_automl): Train a binary classifier on past claims to auto-flag suspect submissions — turn the legacy red-flag-rules engine into a learning model.
- [30-Day Hospital Readmission Risk (AutoML)](https://synapcores.com/recipes/anomaly-detection/004_30day_readmission_automl): Train a classifier to flag patients at high risk of 30-day readmission at discharge time — directly attacks the CMS Hospital Readmissions Reduction Program penalty.
- [API Latency Spike Detection (3-sigma)](https://synapcores.com/recipes/anomaly-detection/005_api_latency_3sigma): Catch latency-spike anomalies with pure SQL Z-scores — no model training, no infra, runs against any AIDB instance.
- [Manufacturing Sensor Drift Detection (per-machine baseline)](https://synapcores.com/recipes/anomaly-detection/006_factory_sensor_drift): Catch silent equipment drift by comparing each sensor reading to that machine's own historical mean/sigma — the Industry-4.0 pattern that beats global thresholds.
- [Patient Vital-Sign Anomaly (per-patient baseline)](https://synapcores.com/recipes/anomaly-detection/007_patient_vitals_personal_baseline): Catch HR spikes against each patient's own personal baseline — the clinical pattern that beats fleet-wide thresholds and prevents alert fatigue.
- [Smart-Meter Tampering Detection (sudden-drop)](https://synapcores.com/recipes/anomaly-detection/008_smart_meter_tampering): Catch electricity-meter tampering by flagging hours where consumption suddenly drops to near-zero — the utility-fraud pattern that costs the global grid $96B/year.
- [Insurance Narrative Fraud Detection (semantic)](https://synapcores.com/recipes/anomaly-detection/009_insurance_narrative_semantic): Use EMBED + COSINE_SIMILARITY to catch claim narratives that semantically match known fraud patterns — the unstructured-data side of SIU fraud detection.

### audio-podcasts
- [Basic Audio Storage](https://synapcores.com/recipes/026_basic_audio_storage): Create a simple table for MP3 audio files with essential metadata for audio file management
- [Multi-Format Audio Library](https://synapcores.com/recipes/027_multi_format_audio_library): Store audio files in multiple formats including MP3, WAV, FLAC, AAC, and OGG for comprehensive audio management
- [Podcast Episode Manager](https://synapcores.com/recipes/028_podcast_episode_manager): Store podcast episodes with show relationships for building a complete podcast management system
- [Music Track Catalog](https://synapcores.com/recipes/029_music_track_catalog): Create a music library with artist and album relationships for comprehensive music management
- [Voice Recording Storage](https://synapcores.com/recipes/031_voice_recording_storage): Store voice memos and recordings with timestamps for personal and business voice note management
- [Podcast Search by Transcript](https://synapcores.com/recipes/033_podcast_search_by_transcript): Search podcast content via transcribed text for discovering episodes by spoken content
- [Audiobook Chapter Management](https://synapcores.com/recipes/034_audiobook_chapter_management): Organize audiobook chapters with sequential ordering for complete audiobook library management
- [Call Recording Archive](https://synapcores.com/recipes/035_call_recording_archive): Store customer service call recordings with metadata for compliance and quality assurance
- [Audio Playlist System](https://synapcores.com/recipes/036_audio_playlist_system): Create playlists with ordered audio tracks for music and podcast playlist management
- [Sound Effect Library](https://synapcores.com/recipes/037_sound_effect_library): Catalog sound effects with categories and tags for game development and media production
- [Meeting Recording Storage](https://synapcores.com/recipes/039_meeting_recording_storage): Store meeting recordings with attendee metadata for corporate meeting management
- [Audio Language Detection](https://synapcores.com/recipes/040_audio_language_detection): Store audio files with detected language from transcription for multilingual content management

### core-foundations
- [Hello World Table](https://synapcores.com/recipes/001_hello_world_table): Create your first AIDB table with basic data types - the essential starting point for learning AIDB SQL
- [Multi-Type Table](https://synapcores.com/recipes/002_multi_type_table): Create a table using all standard SQL types including INTEGER, VARCHAR, BOOLEAN, DECIMAL, and more
- [Multimedia Column Types](https://synapcores.com/recipes/003_multimedia_column_types): Create a table with AUDIO, VIDEO, IMAGE, and PDF columns for storing rich media content
- [Vector Column Basics](https://synapcores.com/recipes/004_vector_column_basics): Create a table with VECTOR type for storing embeddings and enabling similarity search
- [Primary Keys and Constraints](https://synapcores.com/recipes/005_primary_keys_constraints): Create tables with PRIMARY KEY, UNIQUE, NOT NULL, and CHECK constraints for data integrity
- [Foreign Key Relationships](https://synapcores.com/recipes/006_foreign_key_relationships): Create related tables with FOREIGN KEY constraints to establish referential integrity
- [Default Values](https://synapcores.com/recipes/007_default_values): Create tables with DEFAULT values for automatic population of columns
- [JSON and JSONB Columns](https://synapcores.com/recipes/008_json_jsonb_columns): Create tables with JSON and JSONB columns for flexible metadata and semi-structured data storage
- [UUID Primary Keys](https://synapcores.com/recipes/009_uuid_primary_keys): Create tables using UUID for distributed-friendly unique identifiers instead of sequential integers
- [Timestamp Tracking](https://synapcores.com/recipes/010_timestamp_tracking): Create tables with created_at and updated_at timestamp columns for automatic record tracking

### cybersecurity
- [Attack-Path Analysis — What Can a Compromised Host Reach?](https://synapcores.com/recipes/cybersecurity/01_attack_path_graph): Answer the blast-radius question — which crown-jewel assets a compromised host can reach — in a single graph traversal, not a recursive SIEM query.
- [Correlate a New Alert Against Prior Incidents by Meaning](https://synapcores.com/recipes/cybersecurity/02_ioc_semantic_correlation): Match a fresh alert's behavior description against your threat-intel and past-incident corpus by semantic similarity — catch the near-matches that keyword and exact-IOC rules miss.
- [A Write-Once, Append-Only Audit of Every Automated Action](https://synapcores.com/recipes/cybersecurity/03_write_once_action_audit): Record every enrichment, agent action and proposed response in a hash-chained immutable table — the write-once, append-only audit modern agentic-SOC guidance says must live outside the automation platform.
- [Resolve One Actor Across Usernames, Hosts and Artifacts](https://synapcores.com/recipes/cybersecurity/04_entity_resolution): Collapse the same adversary behavior seen under different usernames and hosts into one entity by semantic similarity of the behavior — cut the noise before you page a human.

### database
- [Financial Audit Trail (Immutable)](https://synapcores.com/recipes/database/003_financial_audit_trail_immutable): Quit demo to show the capabilities of IMMUTABLE tables and security features!

### document-processing
- [PDF Document Storage](https://synapcores.com/recipes/056_pdf_document_storage): Store and manage PDF documents with metadata for document management systems
- [PDF Text Extraction](https://synapcores.com/recipes/057_pdf_text_extraction): Extract and search text content from PDF documents using AI
- [Multi-Page PDF Processing](https://synapcores.com/recipes/058_multi_page_pdf_processing): Process multi-page PDF documents with page-level metadata and content tracking
- [Document Embedding Search](https://synapcores.com/recipes/059_document_embedding_search): Use vector embeddings for semantic document search and similarity matching
- [Invoice Data Extraction](https://synapcores.com/recipes/060_invoice_data_extraction): Extract and store structured data from invoice PDF documents
- [Legal Document Repository with Contract Tracking](https://synapcores.com/recipes/061_legal_document_repository): Store and manage legal documents with contract tracking and compliance features
- [Document Version Control](https://synapcores.com/recipes/062_document_version_control): Track document versions with change history and revision management
- [Contract Management System](https://synapcores.com/recipes/063_contract_management_system): Manage contracts with parties, terms, obligations, and renewal tracking
- [Resume/CV Database](https://synapcores.com/recipes/064_resume_cv_database): Store and search candidate resumes with skills extraction and matching
- [Academic Paper Repository](https://synapcores.com/recipes/065_academic_paper_repository): Store research papers with citations, authors, and semantic search capabilities
- [Document Classification](https://synapcores.com/recipes/066_document_classification): Automatically classify documents into categories using AI and rule-based systems
- [Form Data Extraction](https://synapcores.com/recipes/067_form_data_extraction): Extract structured data from PDF forms including fields, values, and validation
- [Document Workflow System](https://synapcores.com/recipes/068_document_workflow_system): Manage document approval workflows with routing, tasks, and audit trails
- [Knowledge Base with PDFs](https://synapcores.com/recipes/069_knowledge_base_with_pdfs): Build a searchable knowledge base from PDF documents using AI embeddings
- [Document Compliance Tracking](https://synapcores.com/recipes/070_document_compliance_tracking): Track document compliance requirements with retention policies and audit trails

### e-commerce-media
- [Product Image Gallery](https://synapcores.com/recipes/071_product_image_gallery): Manage product images with multiple views, variants, and quality levels for e-commerce
- [Product Video Demos](https://synapcores.com/recipes/072_product_video_demos): Manage product demonstration videos with timestamps and feature highlights
- [User-Uploaded Product Reviews with Images](https://synapcores.com/recipes/073_user_uploaded_product_reviews): Manage customer reviews with photos and ratings for social proof
- [Brand Asset Library](https://synapcores.com/recipes/074_brand_asset_library): Manage brand assets including logos, guidelines, and marketing materials
- [Product Comparison Images](https://synapcores.com/recipes/075_product_comparison_images): Create and manage product comparison visuals for helping customers decide
- [Promotional Banner Management](https://synapcores.com/recipes/076_promotional_banner_management): Manage seasonal promotions, campaign banners, and marketing visuals
- [Size Guide with Images](https://synapcores.com/recipes/077_size_guide_images): Create visual size guides with measurement images and fit recommendations
- [Product Unboxing Video Library](https://synapcores.com/recipes/080_product_unboxing_videos): Manage unboxing videos showing product packaging and first impressions

### education-elearning
- [Course Video Library](https://synapcores.com/recipes/096_course_video_library): Organize and manage educational course videos with chapters, transcripts, and progress tracking
- [Lecture Recording Management](https://synapcores.com/recipes/097_lecture_recording_management): Manage university lecture recordings with scheduling, multi-camera capture, and searchable transcripts
- [Student Assignment Submissions](https://synapcores.com/recipes/098_student_assignment_submissions): Manage multimedia student assignment submissions with versioning and feedback
- [Educational Slide Decks](https://synapcores.com/recipes/099_educational_slide_decks): Manage presentation slides with versioning, annotations, and student notes
- [Quiz and Assessment Media](https://synapcores.com/recipes/100_quiz_assessment_media): Create multimedia quizzes with images, audio, and video questions
- [Virtual Classroom Recordings](https://synapcores.com/recipes/101_virtual_classroom_recordings): Manage online class recordings with breakout rooms, chat logs, and participant tracking
- [Educational Resource Library](https://synapcores.com/recipes/102_educational_resource_library): Build a comprehensive multimedia learning resource library with categorization and recommendations

### enterprise-content
- [Corporate Training Videos](https://synapcores.com/recipes/103_corporate_training_videos): Manage employee training content with completion tracking and certification
- [Marketing Asset Management](https://synapcores.com/recipes/104_marketing_asset_management): Organize marketing assets across campaigns with versioning, approvals, and usage tracking
- [Corporate Communications Archive](https://synapcores.com/recipes/105_corporate_communications_archive): Archive and search corporate communications including memos, announcements, and recordings
- [Product Documentation Library](https://synapcores.com/recipes/106_product_documentation_library): Manage technical product documentation with versioning, localization, and feedback
- [Enterprise Legal & Compliance Document Repository](https://synapcores.com/recipes/107_legal_document_repository): Manage legal contracts, agreements, and compliance documents with expiration tracking
- [Brand Asset Guidelines](https://synapcores.com/recipes/108_brand_asset_guidelines): Manage brand guidelines, logos, and visual identity assets with usage rules
- [Employee Onboarding Media](https://synapcores.com/recipes/109_employee_onboarding_media): Manage new hire onboarding content including videos, documents, and checklists
- [Meeting Recordings Archive](https://synapcores.com/recipes/110_meeting_recordings_archive): Archive and search corporate meeting recordings with transcripts and action items

### government
- [An Accountable, Tamper-Evident Record of Every Agent Action — In the Enclave](https://synapcores.com/recipes/government/01_immutable_agent_audit): Keep a hash-chained immutable record of every automated action inside a self-hosted, air-gappable deployment — accountable AI with no external dependency and no data egress.
- [Entity Link Analysis on a Graph — Who Connects to Whom](https://synapcores.com/recipes/government/02_entity_link_graph): Model entities and their relationships as a property graph and traverse the network from a subject of interest — link analysis in one query, fully self-hosted.
- [Grounded Retrieval Over a Controlled Corpus — Fully Offline](https://synapcores.com/recipes/government/03_grounded_offline_rag): Retrieve the most relevant passage for a question from a controlled document corpus by semantic similarity, so an answer is grounded in a citable in-enclave source — local inference, no external AI, no egress.

### graph
- [Hello Graph: Friend-of-Friend](https://synapcores.com/recipes/graph/001_hello_graph): Build a 6-person social graph and find friends-of-friends with a single Cypher pattern match
- [Org Chart: Find everyone under a VP](https://synapcores.com/recipes/graph/002_org_chart_reachability): Traverse a 4-level reporting hierarchy with variable-length paths to list every direct and indirect report
- [Movie recommendation by shared genre](https://synapcores.com/recipes/graph/003_movie_recommendation): Recommend movies a user has not seen by traversing watched-movies and shared-genre patterns
- [Product co-purchase, customers also bought](https://synapcores.com/recipes/graph/004_product_co_purchase): Build an order-product-customer graph and surface the top items frequently bought with a target product
- [Friend-of-friend recommendation with strength](https://synapcores.com/recipes/graph/005_friend_of_friend_recs): Use weighted edges and mutual-friend counts to suggest new connections ranked by tie strength
- [Fraud ring detection in under 50ms](https://synapcores.com/recipes/graph/006_fraud_ring_detection): Detect circular money-laundering patterns up to length 4 by finding cycles in a transaction graph
- [Supply chain blast radius of a vendor failure](https://synapcores.com/recipes/graph/007_supply_chain_impact): Trace which products and customers are affected if a critical vendor goes offline
- [Drug interaction network for patient safety](https://synapcores.com/recipes/graph/008_drug_interaction): Flag dangerous drug combinations across all patients via a prescribed-drug interaction graph
- [RBAC effective permissions through group inheritance](https://synapcores.com/recipes/graph/009_permission_inheritance): Resolve what a user can actually do by walking user-group-role-permission graph paths
- [DAG, find critical build dependencies](https://synapcores.com/recipes/graph/010_dag_dependency): Topologically order a software dependency graph and find the longest critical path
- [Citation network, most influential paper](https://synapcores.com/recipes/graph/011_knowledge_graph_citation): Rank papers by citation influence using a multi-hop weighted graph traversal
- [Identity resolution, merge duplicate customers](https://synapcores.com/recipes/graph/012_identity_resolution): Cluster duplicate customer records that share emails, phones, or addresses across systems
- [Anti-money-laundering layering detection](https://synapcores.com/recipes/graph/013_money_laundering): Surface multi-hop transaction chains that obscure source-of-funds, longer than 3 hops with high values
- [Knowledge graph QA, who founded the iPhone maker](https://synapcores.com/recipes/graph/015_kg_qa): Answer multi-hop natural-language questions by traversing a small entity graph
- [GraphRAG, hybrid vector + graph multi-hop QA](https://synapcores.com/recipes/graph/016_graphrag_qna): Combine SIMILAR_TO vector hops with structural patterns to answer questions vector-only RAG can't
- [Earnings-call transcript to knowledge graph](https://synapcores.com/recipes/graph/017_extract_earnings_call): Send a paragraph of a CFO call to /v2/graph/extract and query the resulting entity graph
- [Contract clause graph with LLM-judged risk](https://synapcores.com/recipes/graph/018_extract_legal_contract): Extract parties, obligations, and dates from contract text, then have LLM_SCORE flag risky clauses
- [Semantic product recommendations with SIMILAR_TO](https://synapcores.com/recipes/graph/019_semantic_product_recs): Recommend "products like this" by walking SIMILAR_TO over embedding properties on Product nodes
- [Agentic memory graph for an AI assistant](https://synapcores.com/recipes/graph/020_agentic_memory): Build a long-term episodic memory graph for an LLM agent, recall by semantic + structural patterns
- [Talent matching, resume to job by skill graph + embedding](https://synapcores.com/recipes/graph/021_resume_to_job): Match candidates to roles with structural skill hits plus semantic similarity and an LLM fit score
- [Semantic identity resolution beyond exact match](https://synapcores.com/recipes/graph/022_semantic_dedup): Catch duplicate customers whose emails differ but whose name + address embed alike
- [Threat-intel correlation across feeds](https://synapcores.com/recipes/graph/023_threat_intel_correlation): Cluster IOCs and actors across feeds by extracting from advisories and matching with SIMILAR_TO
- [Supply-chain risk from news headlines](https://synapcores.com/recipes/graph/024_supply_chain_news): Extract supplier-event edges from news prose and grade each event with LLM_SCORE
- [Drug repurposing via mechanism similarity](https://synapcores.com/recipes/graph/025_drug_repurposing): Walk drug-target-disease chains then use SIMILAR_TO on mechanism embeddings to find candidates
- [Literature review graph from paper abstracts](https://synapcores.com/recipes/graph/026_research_lit_review): Extract entities from abstracts and cluster papers semantically with SIMILAR_TO
- [Rank community influencers with LLM authenticity](https://synapcores.com/recipes/graph/027_influencer_ranking): Combine connection-count centrality with LLM_SCORE for authenticity, surface real influencers
- [Code dependency CVE relevance with LLM_SCORE](https://synapcores.com/recipes/graph/028_code_dependency_risk): Walk transitive dependency edges and have the LLM judge if a CVE actually applies in your context
- [Find similar patients by symptom embedding](https://synapcores.com/recipes/graph/029_clinical_patient_similarity): Use SIMILAR_TO over symptom embeddings on patient nodes to surface clinical lookalikes
- [Meeting minutes to action-item graph](https://synapcores.com/recipes/graph/030_meeting_minutes_kg): Extract action items, owners, and dates from meeting minutes and rank urgency with LLM_SCORE
- [GraphRAG vs Neo4j: a customer-360 knowledge graph that recommends the next action](https://synapcores.com/recipes/graph/graphrag-vs-neo4j-customer-360-qa): Build a customer-360 knowledge graph in one database — an at-risk account's open ticket finds the resolution that fixed a similar past case, weighted by the account's tier and ARR, in a single Cypher query — and see what the same thing costs on a Neo4j + vector-DB stack.
- [GraphRAG vs Neo4j: fraud-ring detection across accounts, devices, and behavior](https://synapcores.com/recipes/graph/graphrag-vs-neo4j-fraud-ring-detection): Catch organized fraud rings in one Cypher query — shared devices and addresses (graph structure) plus behavioral similarity (vector hop) plus LLM risk scoring — and see what the same detection costs on a Neo4j + vector-DB stack.
- [GraphRAG vs Neo4j: a knowledge base that answers multi-hop questions](https://synapcores.com/recipes/graph/graphrag-vs-neo4j-knowledge-base): Build a GraphRAG knowledge base in one database — semantic search, graph traversal, and LLM ranking in a single Cypher query — and see exactly what the same thing costs on a Neo4j + vector-DB stack.
- [GraphRAG vs Neo4j: product recommendations that blend co-purchase and semantics](https://synapcores.com/recipes/graph/graphrag-vs-neo4j-product-recommendations): Build cross-sell recommendations in one database — co-purchase traversal, semantic similarity, and LLM scoring in a single Cypher query — that keep working on brand-new SKUs with zero purchase history, and see what the same thing costs on a Neo4j + vector-DB stack.
- [GraphRAG vs Neo4j: supply-chain impact analysis and part substitution](https://synapcores.com/recipes/graph/graphrag-vs-neo4j-supply-chain-impact): Answer "what breaks if a supplier fails, and what can we substitute?" in one Cypher query — graph traversal to the products at risk plus a semantic hop to viable alternative parts — and see what the same thing costs on a Neo4j + vector-DB stack.

### healthcare
- [Ground Clinical Answers in Your Own Guidelines — Retrieval by Meaning](https://synapcores.com/recipes/healthcare/01_grounded_clinical_retrieval): Retrieve the most relevant guideline or chart passage for a clinical question by semantic similarity, so a decision-support answer is grounded in a citable source instead of model priors — self-hosted, PHI never leaves.
- [Find Clinically Similar Patients by Meaning](https://synapcores.com/recipes/healthcare/02_patient_similarity_cohort): Retrieve patients whose presentation is clinically similar to an index case, for cohorting and case comparison — semantic similarity over the presentation summary, self-hosted.
- [Tamper-Evident Clinical Decision-Support Lineage (ONC HTI-1)](https://synapcores.com/recipes/healthcare/03_immutable_cds_lineage): Record every AI-assisted clinical suggestion — model, version, cited sources, clinician action — in a hash-chained immutable table, the source-attribute and intervention-transparency trail ONC HTI-1 expects.

### healthcare-imaging
- [Medical Image Storage](https://synapcores.com/recipes/081_medical_image_storage): Store and manage medical images with patient records and metadata
- [X-Ray Image Management](https://synapcores.com/recipes/082_xray_image_management): Organize and manage radiographic X-ray images with views and annotations
- [CT and MRI Scan Organization](https://synapcores.com/recipes/083_ct_mri_scan_organization): Manage complex cross-sectional imaging studies with multiple sequences and reconstructions
- [Pathology Slide Images](https://synapcores.com/recipes/084_pathology_slide_images): Manage whole slide images for digital pathology and tissue analysis
- [Medical Image Annotation](https://synapcores.com/recipes/085_medical_image_annotation): Create and manage annotations, measurements, and findings on medical images
- [Patient Imaging History](https://synapcores.com/recipes/086_patient_imaging_history): Track and query patient imaging studies over time for longitudinal analysis
- [Radiology Report Integration](https://synapcores.com/recipes/087_radiology_report_integration): Link radiology reports with images and extract structured findings
- [Medical Image Analytics](https://synapcores.com/recipes/088_medical_image_analytics): Analyze medical imaging data for operational insights and quality metrics

### image-management
- [Multi-Format Image Library](https://synapcores.com/recipes/012_multi_format_image_library): Store images in multiple formats including JPEG, PNG, WEBP, and GIF with format-specific columns
- [Image with Metadata](https://synapcores.com/recipes/013_image_with_metadata): Store images with dimensions, file size, and EXIF data in JSON columns for rich metadata management
- [Photo Album Organization](https://synapcores.com/recipes/014_photo_album_organization): Create albums and photos tables with relationships for organizing images into collections
- [Image Tagging System](https://synapcores.com/recipes/015_image_tagging_system): Implement a flexible tagging system for images using a junction table for many-to-many relationships
- [Profile Picture Storage](https://synapcores.com/recipes/016_profile_picture_storage): Store user profile pictures with thumbnail variants for efficient display at different sizes
- [Image OCR Extraction](https://synapcores.com/recipes/017_image_ocr_extraction): Extract text from images using the EXTRACT_TEXT function for searchable image content
- [Image Dimension Query](https://synapcores.com/recipes/018_image_dimension_query): Query images by dimensions using the DIMENSIONS function for filtering by size and aspect ratio
- [Image Embedding Search](https://synapcores.com/recipes/019_image_embedding_search): Create embeddings for images to enable similarity search and visual content discovery
- [Screenshot Archive](https://synapcores.com/recipes/020_screenshot_archive): Store and organize application screenshots with metadata for bug tracking and documentation
- [Product Image Variants](https://synapcores.com/recipes/021_product_image_variants): Store multiple image sizes for e-commerce products including thumbnails, medium, and full-size variants
- [Scanned Document Images](https://synapcores.com/recipes/024_scanned_document_images): Store scanned documents as images with OCR text extraction for searchable document archives

### insurance
- [Adverse-Action Decision Records with Reason Codes, Tamper-Evident](https://synapcores.com/recipes/insurance/01_adverse_action_decision_record): Record every underwriting decision — score, model version, ECOA reason codes, human override — in a hash-chained immutable table, so the adverse-action notice and the examiner evidence come from the same verifiable source.
- [Disparate-Impact Testing — the Four-Fifths Rule in One Query](https://synapcores.com/recipes/insurance/02_disparate_impact_testing): Measure approval rates across protected groups and flag a disparate-impact problem with a single SQL query over the decisions you already made — continuous fairness testing for NAIC, Colorado and DOI review.
- [Find Similar Prior Claims by Narrative — Triage and Fraud Signal](https://synapcores.com/recipes/insurance/03_claim_narrative_similarity): Retrieve the most semantically similar past claims for a new one — surface likely-related or suspicious claims that share a story, not just a keyword, so adjusters triage consistently.

### legal
- [Flag Risky Clauses by Meaning Against Your Playbook](https://synapcores.com/recipes/legal/01_clause_risk_search): Score a contract's clauses against your risk playbook by semantic similarity to surface the risky, non-standard, or missing language — self-hosted, so privileged documents never leave.
- [Turn a Contract Into a Queryable Obligation Graph](https://synapcores.com/recipes/legal/02_obligation_graph): Model a contract's obligations — trigger, deadline, remedy — as a property graph, then answer 'what is due this quarter?' across the whole book in one query.
- [A Defensible, Tamper-Evident Record of Every AI-Assisted Review](https://synapcores.com/recipes/legal/03_immutable_review_audit): Log every AI-assisted contract or e-discovery review — document, model version, flags raised, reviewer decision — in a hash-chained immutable table, for a defensible and demonstrably consistent process.

### ml
- [Hello World: Linear Regression (y = 2x + 1)](https://synapcores.com/recipes/ml/001_hello_world_linear_regression): Train a simple regression model, deploy it, run predictions, then verify results match the known function.
- [Customer Churn Prediction](https://synapcores.com/recipes/ml/002_customer_churn_prediction): Build a model to predict which customers are likely to churn based on their account characteristics and usage patterns.
- [Drug Discovery Candidate Selection](https://synapcores.com/recipes/ml/005_drug_discovery_candidate_selection): Score compounds for likelihood of success. Prioritize top candidates for lab testing.
- [Real Estate AI: Property Matching & Market Analysis](https://synapcores.com/recipes/ml/006_real_estate_ai_matching): Build an intelligent real estate platform that matches buyers with properties, predicts market trends, analyzes property values, and generates insi...
- [AI-Driven Marketing & Customer Insights](https://synapcores.com/recipes/ml/007_ai_marketing_customer_insights): Create intelligent marketing campaigns by analyzing customer behavior, segmenting audiences, predicting churn, and generating personalized content...

### pharmacovigilance
- [Catch Duplicate & Related Adverse-Event Reports by Meaning](https://synapcores.com/recipes/pharmacovigilance/01_icsr_duplicate_detection): Find near-duplicate and related ICSRs before they inflate your case counts — semantic similarity over the report narrative, in one SQL query, no external vector store.
- [MedDRA Coding Assist — Verbatim Term to Preferred Term by Meaning](https://synapcores.com/recipes/pharmacovigilance/02_meddra_coding_assist): Suggest MedDRA Preferred Terms from a reporter's free-text verbatim by semantic similarity, ranked for a coder to confirm — consistent coding without a brittle keyword dictionary.
- [Source-Grounded ICSR Drafting — the Model Proposes, a Human Approves](https://synapcores.com/recipes/pharmacovigilance/03_source_grounded_icsr_draft): Draft an adverse-event narrative from structured case fields with SELECT GENERATE, then keep the human-in-the-loop review and the immutable audit that make it safe for a regulated safety workflow.
- [An Inspection-Ready, Tamper-Evident Audit Ledger for AI-Assisted PV](https://synapcores.com/recipes/pharmacovigilance/04_immutable_pv_audit_ledger): Record every AI-assisted drafting and coding decision — source, model version, reviewer, outcome — in a cryptographically hash-chained, encrypted-at-rest immutable table an FDA/EMA inspector can verify.

### security-surveillance
- [Security Camera Video Storage](https://synapcores.com/recipes/089_security_camera_video_storage): Store and manage surveillance video footage from security cameras
- [Access Control Logs with Images](https://synapcores.com/recipes/091_access_control_logs): Track access control events with badge photos and entry images
- [License Plate Recognition](https://synapcores.com/recipes/092_license_plate_recognition): Store and query license plate recognition data from parking and security systems
- [Facial Recognition Logging](https://synapcores.com/recipes/093_facial_recognition_logging): Log and query facial recognition events for access control and security
- [Incident Video Evidence](https://synapcores.com/recipes/094_incident_video_evidence): Manage video evidence collection and chain of custody for security incidents
- [Security Alert Management](https://synapcores.com/recipes/095_security_alert_management): Manage security alerts, notifications, and response workflows

### video-streaming
- [Basic Video Storage - MP4](https://synapcores.com/recipes/041_basic_video_storage_mp4): Store and retrieve MP4 video files with metadata for video content management
- [Multi-Format Video Library](https://synapcores.com/recipes/042_multi_format_video_library): Store videos in multiple formats (MP4, AVI, MKV, WEBM, MOV) for cross-platform compatibility
- [Video Duration Query](https://synapcores.com/recipes/043_video_duration_query): Query and analyze video content by duration for content planning and scheduling
- [Video Frame Extraction](https://synapcores.com/recipes/044_video_frame_extraction): Extract and store video frames for thumbnails, previews, and image analysis
- [Video Audio Track Extraction](https://synapcores.com/recipes/045_video_audio_track_extraction): Extract and manage audio tracks from video files for transcription and analysis
- [Video Transcription](https://synapcores.com/recipes/046_video_transcription): Transcribe video content to text for searchability, subtitles, and accessibility
- [Video Chapter Markers](https://synapcores.com/recipes/047_video_chapter_markers): Add chapter markers to videos for enhanced navigation and content organization
- [Video Thumbnail Storage](https://synapcores.com/recipes/048_video_thumbnail_storage): Store multiple thumbnail images for video content with selection preferences
- [Video Category Organization](https://synapcores.com/recipes/049_video_category_organization): Organize videos into hierarchical categories with tags for content discovery
- [Video Series Management](https://synapcores.com/recipes/050_video_series_management): Manage video series with episodes, seasons, and sequential ordering
- [User-Generated Video Platform](https://synapcores.com/recipes/051_user_generated_video_platform): Build a platform for user-uploaded videos with moderation and engagement features
- [Video View Tracking](https://synapcores.com/recipes/052_video_view_tracking): Track video views with detailed analytics including watch time and completion rates
- [Video Subtitle Storage](https://synapcores.com/recipes/053_video_subtitle_storage): Store multi-language subtitles and captions for video accessibility

### voice-agents
- [Build a Voice Support Agent (memory + routing + RAG)](https://synapcores.com/recipes/voice-agents/build-a-voice-support-agent): Build a complete voice support agent on one database — caller memory, real-time skill routing, RAG-grounded spoken answers, an urgency model, and a semantic cache, all in SQL. The brain for any STT/TTS stack (Vapi, LiveKit, Twilio, Pipecat).
- [Caller Memory & Personalization (returning callers)](https://synapcores.com/recipes/voice-agents/caller-memory-and-personalization): Make a voice AI agent recognize returning callers — recall their past calls and preferences by meaning and map their account relationships as a graph, so it greets them by context, not a cold script. For any STT/TTS stack (Vapi, LiveKit, Twilio, Pipecat).
- [Conversation Memory for a Voice Agent](https://synapcores.com/recipes/voice-agents/conversation-memory-for-a-voice-agent): Give a voice AI agent memory across a call and between calls — store transcribed turns, recall by meaning, and keep a rolling summary so it never loses the thread. Database-as-the-brain for any STT/TTS stack (Vapi, LiveKit, Twilio, Pipecat).
- [Low-Latency Semantic Answer Cache for Voice](https://synapcores.com/recipes/voice-agents/low-latency-semantic-answer-cache-for-voice): Cut voice AI latency and cost with a semantic answer cache — serve a stored answer when a caller's question means the same as one you've answered before, even if worded differently, with a vector lookup in SQL. For any STT/TTS stack (Vapi, LiveKit, Twilio, Pipecat).
- [Real-Time Intent → Skill Routing for a Voice Agent](https://synapcores.com/recipes/voice-agents/real-time-intent-to-skill-routing-for-a-voice-agent): Route a voice AI agent's caller to the right skill in real time — match the transcribed utterance to a skill by meaning with a vector lookup, fast enough for a live call. Database-as-the-brain for any STT/TTS stack (Vapi, LiveKit, Twilio, Pipecat).
- [Voice-Agent RAG Knowledge Base (ground spoken answers)](https://synapcores.com/recipes/voice-agents/voice-agent-rag-knowledge-base): Ground a voice AI agent's spoken answers in your own knowledge base — retrieve the right passage by meaning and generate a short, speakable, accurate reply, so the agent never makes things up on a call. For any STT/TTS stack (Vapi, LiveKit, Twilio, Pipecat).