PRODUCT

Real-time document intelligence for your AI knowledge base. Monitor quality, identify gaps, and improve your AI's responses.

Quality Dashboard

Real-time performance metrics for your AI knowledge base

Teckel AI Performance Metrics

HOW TECKEL AI WORKS

Three simple steps to transform your AI's accuracy

CONNECT YOUR AI

Add our lightweight SDK to your existing RAG pipeline. Works with any LLM provider in under 15 minutes.

MONITOR QUALITY

Every query is automatically scored. See which documents are performing well and which are causing failures.

IMPROVE DOCUMENTS

Get alerts about gaps and outdated content. Fix the root cause to improve your AI's responses instantly.

BUILT FOR ENTERPRISE AI APPLICATIONS

Whether you're building an internal chatbot or customer-facing AI, Teckel ensures your knowledge base delivers accurate, reliable answers.

HR & BENEFITS CHATBOTS

Ensure employees get accurate information about policies, benefits, and procedures.

Track policy questions
Identify handbook gaps
Monitor compliance queries

PRODUCT SUPPORT AI

Keep product documentation current as features evolve and customer needs change.

Feature usage patterns
Documentation freshness
Support ticket reduction

COMPLIANCE Q&A SYSTEMS

Maintain accurate, up-to-date regulatory information across complex document sets.

Regulatory accuracy
Policy updates tracking
Audit trail generation

SIMPLE INTEGRATION, POWERFUL INSIGHTS

Start tracking knowledge gaps with minimal setup. Our SDK captures query patterns and document usage, giving you the intelligence to continuously improve your AI's ground truth.

INTEGRATION EXAMPLE

1. Install the SDK

npm install @teckel-ai/tracer

2. Initialize with your API key

import { TeckelTracer } from '@teckel-ai/tracer';

const tracer = new TeckelTracer('your-api-key-here');

3. Track any LLM interaction (2-line integration)

// Your existing RAG flow (any LLM provider)

const response = await openai.chat.completions.create({...});

// Add Teckel monitoring (just 2 lines!)

const traceId = await tracer.trace(userQuery, response, {

model: 'gpt-5',

sources: [

{

document_name: 'user-manual.pdf',

document_text: 'Retrieved content...'

}

sessionId: sessionId,

userId: user.email // Optional: track specific users

});

READY TO IMPROVE YOUR AI'S ACCURACY?

Join leading companies using Teckel AI to transform failed queries into better documentation.