What it actually does
Semantica replaces the traditional 'black box' prompt context with a verifiable, graph-native knowledge system. Instead of stuffing a prompt with plain text and hoping the LLM reasons correctly, Semantica forces the AI to output its decisions as causal traces linked directly to nodes in your knowledge graph. You can run `semantica doctor` to audit exactly why an agent made a specific decision, which policy rule it followed, and what data it ignored.
Who it's for
- 01
Enterprise teams building AI agents for regulated industries (finance, healthcare, legal)
- 02
Founders who need to prove to auditors exactly why their AI made a specific decision
- 03
AI engineers struggling to debug hallucinations in complex, multi-step RAG workflows
Where it earns its keep
- Building a loan-approval AI where every rejection must explicitly link to the exact compliance rule that triggered it
- Auditing a customer support bot's conversation history to see which internal policy led to a refund
- Ensuring an AI legal assistant explicitly cites valid precedent nodes rather than hallucinating case law
Use it, or skip it
Reach for it when
- Accountability and auditability are non-negotiable requirements for your product
- You are operating in a strict compliance environment (SOC2, HIPAA, GDPR)
- Your current agents suffer from 'lost in the middle' syndrome and forget rules
Skip it when
- You are building a simple, creative writing bot where strict factual tracing is unnecessary
- Your team doesn't have the bandwidth to map your unstructured data into a formal knowledge graph
10 automations
Ideas, not tutorials. Each one is work a team does by hand today.
- 01Operations
Compliance Audit Trail Generator
Automatically generate a PDF report for every automated customer decision, explicitly diagramming the causal trace of rules that led to the outcome.
- 02Founders
Policy Conflict Detector
Run Semantica across your internal company wiki to flag contradictions between HR policies and engineering guidelines.
- 03Engineering
Automated SOC2 Evidence Collection
Wire your deployment agents to Semantica so every production change is causally linked back to an approved Jira ticket for auditors.
- 04Founders
Legal Contract Reviewer
Scan inbound vendor contracts and highlight clauses that violate your company's master legal graph, providing exact policy citations.
- 05Operations
Support Ticket QA Analyst
Nightly script that reviews all AI-handled support tickets and flags any resolution that deviated from the standard graph-based policy.
- 06Finance
Financial Transaction Screener
Evaluate incoming payments against a graph of known fraud patterns, requiring explicit causal evidence before flagging an account.
- 07Engineering
Engineering Architecture Enforcer
Block PRs that introduce dependencies violating the approved software architecture graph.
- 08Operations
Medical Record Summarizer
Summarize patient histories where every extracted fact contains a strict pointer to the source doctor's note.
- 09Operations
Real Estate Zoning Validator
Assess property development plans against a graph of local zoning laws, outputting a precise list of violations.
- 10Engineering
Automated Privacy Auditor
Map the flow of PII through your codebase and ensure every access point is causally linked to a user consent record.
Want one of these running by Friday?
LimeDock builds these as real workflows inside your stack — deployed to your cloud, wired into your Slack and CRM, with the code in your repo. You pay a build fee and your own API keys, nothing else.
Source
Repository stats were read from the GitHub API and reflect the last time we refreshed this entry. The editorial breakdown above is LimeDock’s own analysis — we are not affiliated with semantica-agi.
https://github.com/semantica-agi/semantica