Terenge

Lead and Reviewer Architecture

The Multi-LLM Iterative Refinement Engine

Automate the creation of high-fidelity technical specifications. We use a "Lead/Reviewer" architecture where one AI drafts, and others (OpenAI, Anthropic, Google) critique for security, logic, and completeness.

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0 specs processed 3 independent reviewer lanes

How It Works

  1. Step 1: Draft.

    Primary model creates the initial document.

  2. Step 2: Peer Review.

    Secondary models cross-validate for single-model bias.

  3. Step 3: Self-Correction.

    Automatically triggers up to multiple refinement cycles until the quality threshold is met.

Draft -> Review -> Refinement

Lead Drafting Reviewer Mesh (OpenAI, Anthropic, Google) Cross-checks security, logic, completeness Refinement Cycle Apply fixes until threshold met
The system loops through reviewer feedback and self-correction automatically, then exits only when quality criteria are satisfied.
FEATURE 01

Cross-Provider Validation

Eliminates single-model bias by using secondary LLMs to peer-review the primary output.

FEATURE 02

Iterative "Self-Correction" Loop

Automated refinement cycles based on reviewer feedback ensure high-quality output without human intervention.

FEATURE 03

Agnostic Integration

Built on a standardized adapter pattern (FastAPI + LiteLLM/LangChain) allowing seamless swapping between top-tier models like GPT-4o and Claude 3.5 Sonnet.

FEATURE 04

Real-Time Monitoring

Watch the intelligence in action. Our Server-Sent Events (SSE) progress tracker lets you view the drafting, reviewing, and refining stages live.