ai·rete·rag
ai·rete·rag is a decision-intelligence platform that combines a deterministic Rete rule engine with retrieval-augmented generation. Rules produce an auditable, repeatable verdict, while retrieval and an LLM provide a grounded plain-language explanation from the user's policy documents.
At a Glance
- Regulated financial-services teams
- Healthcare organizations
- Legal and compliance teams
- Insurance companies
- +4 more
AI Tools by ai·rete·rag
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ai-rete-rag
Rete Rule Engine with RAG
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Latest News
Show HN launch: AI·rete·RAG — a Rete rule engine decides, RAG explains why
ai-rete-rag-mcp v0.7.0 released with an OAuth-protected /mcp/auth endpoint
Published ‘Deterministic verdicts, LLM explanations: why we didn’t let the model decide’
Products & Services
Hosted API and workspace for authoring YAML rules, ingesting policy documents, evaluating facts, and returning verdict, explanation, or full-audit responses. It includes a Rete rule engine, ChromaDB-backed retrieval, an orchestrator, a visual rule editor, policy-rule browsing, decision audits, and conflict detection.
Open-source MIT MCP server/client that lets Claude Code, Claude Desktop, and other MCP clients call ai·rete·rag. It provides tools including decide, list_rules, get_rule_source, import_policy_rules, put_rules, ingest_text, list_documents, and get_usage; it can be installed with uvx or pip.
Market Position
ai·rete·rag positions itself between conventional rule engines and general-purpose LLM/RAG systems: unlike an LLM that both decides and explains, its deterministic Rete engine owns the verdict and audit trace, while the LLM only explains using retrieved policy evidence. Compared with a traditional rule engine, it adds document retrieval, fact extraction, natural-language explanations, and MCP/agent access.
Leadership
Founders
Zahara Hussain
Creator of ai·rete·rag and author of its Show HN launch. Her publicly visible work on the project includes the hosted platform and the open-source ai-rete-rag-mcp client; no prior employers or roles were identified in the sources reviewed.
Executive Team
Zahara Hussain
Founder and creator
Identified publicly as the creator/author of ai·rete·rag through the project's Hacker News launch and GitHub repositories; prior employment history was not established from the reviewed sources.
Founding Story
Zahara Hussain says she built ai·rete·rag after seeing teams put an LLM in charge of decisions that need to be auditable—such as lending, fraud screening, and clinical triage—and then add guardrails afterward. The initial vision was to split the responsibilities: a deterministic Rete engine owns the verdict and trace, while RAG-grounded language generation explains the already-made decision.
Business Model
Revenue Model
Subscription SaaS based on monthly decision volume, domains, and document-storage allowances; there are no per-seat fees. An API is available on every plan, and paid subscriptions are processed by Razorpay.
Pricing Tiers
1 domain, 1,000 decisions/month, 10 MB document storage, all response modes including full_audit, public API, no card required.
3 domains, 10,000 decisions/month, 50 MB document storage, full_audit, public API, team members, and community support.
5 domains, 25,000 decisions/month, 250 MB document storage, full_audit, public API, team members, and email support.
10 domains, 100,000 decisions/month, 1 GB document storage, full_audit, public API, team members, and email support.
Unlimited domains, 500,000 decisions/month, 10 GB document storage, full_audit, rule change tracking, and priority support with a stated under-four-hour SLA.
Unlimited everything, self-hosted deployment option, custom LLM endpoints, dedicated success engineer, custom SLA, and compliance review/BAA on request.
Target Markets
- Regulated financial-services teams
- Healthcare organizations
- Legal and compliance teams
- Insurance companies
- Blockchain and Web3 businesses
- Operations and supply-chain teams
- Loan underwriting and credit decisions
- Fraud screening and transaction risk
- Clinical alerts, medication safety, prior authorization, and triage
- KYC/AML, sanctions screening, and wallet or transfer risk
- Legal and compliance policy enforcement and contract review
- Insurance claims adjudication, risk rating, and eligibility