Now with Code Generator, GitHub scanning, Doc Hub & batch audits

Audit every LLM hallucination in your APIs & docs

Connect your GitHub repo. Audit every LLM hallucination in your API docs. Then generate production-ready integration code in 12 languages — all from one platform.

localhost:3000/dashboard/create-audit
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Connect your GitHub repository

AI will scan for OpenAPI specs and route files, then suggest the highest-priority endpoints.

github.com/stripe/stripe-node
Scan Repo
stripe/stripe-node — scanned 47 files, found 12 endpoints
All|High only
highPOSTCreate Payment Intent
Use →
highGETRetrieve Customer
Use →
mediumPOSTCreate Refund
Use →
2 endpoints selected — click Continue
Back
Continue
500+
Context Hub Docs
8
Wizard Steps
3+
LLM Models Tested
Auto
GitHub PR Deploy
See it in action

Three tools, one platform

Audit LLM hallucinations, generate integration code, and validate your documentation — all without leaving DocuTect.

Step 1 — Select Endpoints
github.com/stripe/stripe-node
Scan
Found 12 endpoints · AI pre-selected high-priority items
POSTCreate Charge
GETRetrieve Customer
POSTCreate Payment Intent
GETList Invoices
Step 2 — Configure
Audit endpoints firstOPTIONAL
Fix inaccurate docs before generating code — ~30 s per endpoint
Output language
🐍Python
🔷TypeScript
🐹Go
Java
🟣C#
⚛️React
🦀Rust
🎯Kotlin
3 endpoints selected · est. $3.00
Generate
Step 3 — Results (Python) Generated
File tree · 6 files
Download all (.zip)
stripe-api/
client.py
endpoints/
↓ folder
charges.py
customers.py
payment_intents.py
models/2 files
↓ folder
charges.py
customers.py
payment_intents.py
import stripe
import os

# API key from environment — never hard-code
stripe.api_key = os.environ["STRIPE_SECRET_KEY"]

def create_charge(
    amount: int,           # cents (e.g. 2000 = $20.00)
    currency: str = "usd",
    source: str = None,
    description: str = "",
) -> stripe.Charge:
    """Create a Stripe charge.
    Docs: stripe.com/docs/api/charges/create
    """
    return stripe.Charge.create(
        amount=amount,
        currency=currency,
        source=source,
        description=description,
    )
Copy
Preview
Audit-verified · 97% accuracy
Is this for me?

Built for teams whose API is the product

DocuTect is purpose-built for organisations and individuals who ship developer-facing APIs and documentation — and who care whether the world's most-used LLMs describe them correctly.

API-first companies

Platforms whose product surface is an API. When your developer experience is your product, hallucinated answers in LLMs are silent revenue leakage — DocuTect surfaces them before your users hit them.

Technology & SaaS teams

Engineering organisations shipping public or partner APIs. Quantify how accurately Claude, GPT-4 and Gemini describe your endpoints, and remediate the gaps with measurable, auditable changes.

Developers & DevRel

Individual maintainers and developer-relations teams responsible for SDKs, reference docs and quickstarts. Catch drift between your code and your docs every time you ship.

Teams building with LLMs

If you generate APIs, schemas, or documentation with the help of LLMs, DocuTect closes the loop — auditing AI-authored content against the live system it claims to describe.

API integrators

Developers whose job is connecting systems — consuming Stripe, Twilio, Plaid, or dozens of other third-party APIs. DocuTect scans the API source and generates production-ready integration code in your language of choice, so you spend time on product logic, not reading docs.

Developers connecting products to services

Building a product that talks to external services via API? DocuTect generates accurate, audit-first integration code — so the code you paste into your codebase matches the actual API behaviour, not what the docs say it does.

In short: if you ship developer-facing APIs, integrate with third-party services, or connect your product to external APIs — DocuTect helps you do it accurately, confidently, and fast.

Why DocuTect

The first platform to close the entire loop

Most tools stop at evaluation. DocuTect ships every stage as one integrated workflow — from GitHub repo scan all the way to a merged pull request with fixed documentation.

New

API Code Generator

Scan any GitHub repo or docs URL, select API endpoints, optionally audit first, then generate ready-to-run integration code in Python, TypeScript, Go, Java, C# and 8 more languages.

New

AI Documentation Generator

Point at a GitHub repo, upload source files, or paste code — DocuTect generates a complete OpenAPI 3.1 spec and Markdown reference following Microsoft, Google AIP, AWS, and RFC 7807 standards.

New

In-App AI Assistant

A built-in chatbot answers questions about your audits, finds endpoints, and walks you through remediation — without leaving the dashboard.

New

Encrypted Token Vault

GitHub tokens and integration secrets are stored with envelope encryption and per-repo scoping. Connections are isolated and rotation-friendly.

New

AI-Powered GitHub Scan

Point DocuTect at any GitHub repo. AI scans your codebase, discovers API endpoints and docs, and pre-selects the highest-priority items for you.

New

Documentation Hub

Validate .md, .rst, and .txt documentation files for accuracy, completeness, and consistency. Browse 500+ docs from the Context Hub registry.

New

Ground Truth Bundles

Combine OpenAPI specs, live API probes, GitHub repo scans, and manual notes into a tiered, weighted source of truth that every audit measures against.

New

Batch Audits

Queue dozens of API endpoints or doc files in a single run. The 8-step wizard guides you from intake to GitHub PR in minutes.

New

One-Click PR Deploy

After auditing, push AI-generated remediation fixes straight back to GitHub as a pull request — no manual copy-paste required.

Synthetic Query Generation

AI generates realistic edge-case developer questions covering timeout handling, auth failures, rate limits, and more.

Multi-Model Testing

Every query is fired at GPT-4.1, Claude 4 Sonnet, and Gemini 2.5 Flash simultaneously. Compare responses side by side.

Hallucination Detection

A judge LLM evaluates every response against your documentation, flagging fabricated endpoints, wrong parameters, and invented behavior.

Scheduled Recurring Audits

Set audits to run daily, weekly, or monthly. DocuTect alerts you when scores drop — catch regressions before your users do.

Model Leaderboard

Compare accuracy scores, hallucination rates, latency, and token usage across every model in a ranked leaderboard.

Judge Reasoning

For every evaluation, see exactly why a response was scored the way it was — with specific hallucination details and missing context.

Remediation Engine

Auto-generates prioritized, actionable documentation fixes based on hallucination patterns — with concrete wording you can copy-paste.

Automated Pipeline

One click to audit. DocuTect handles query generation, multi-model interrogation, evaluation, and remediation automatically.

Capability
Typical tools
DocuTect
Automated query generation
Multi-model hallucination scoring
GitHub repo discovery
Scheduled recurring audits
Batch audits across endpoints
Tiered Ground Truth bundles
Auto-generated PR remediation
API integration code generation
Enterprise controls & team access
How much would it cost?

Price your usage in seconds

Choose a tier, set your expected audits per month, and see your bill instantly. As a guide, one API endpoint = one audit per scheduled run.

Estimate your monthly cost

Guide: 1 API endpoint = 1 audit. One scheduled run of one endpoint counts as a single audit.

50 included · overages at $3/audit

Max 10,000 audits per month

Your estimate

$100/ month
Pro plan$100
Included audits25 / 50
Overage (0 × $3)$0
Annual cost$1200
Start Pro trial

Estimate only. Final pricing applies at checkout. Overage capped at 5 additional audits per month and billed at month-end.

View full pricing details & FAQ

LLMs make things up about your API

Foundational models hallucinate incorrect endpoints, wrong authentication methods, outdated parameters, and completely fabricated configuration steps. Your developers trust these answers — and file support tickets when they fail.

Invented API endpoints that don't exist
Wrong authentication methods and headers
Outdated parameters and deprecated patterns
Fabricated error codes and response formats
Inconsistencies between API and documentation
Audit Results — POST /v1/payment_intents
gpt-4.1
34%critical
Invented "secret_key" body param; actual auth is via Authorization header
claude-4-sonnet
92%Clean
gemini-2.5-flash
71%medium
Wrong currency format — stated "USD" string, actual is lowercase "usd"
Remediation suggested: Update auth docs to specify Authorization: Bearer sk_live_… header only.

From repo to fixed docs in 6 steps

The guided wizard takes you all the way from connecting GitHub to shipping a remediation PR.

01

Choose Audit Type

Pick API Hub or Documentation Hub. Then select your input method — manual, GitHub repo, file upload, or generate fresh OpenAPI docs from your code.

02

AI Discovers Content

Connect your GitHub repo and AI scans for endpoints and docs, pre-selecting the highest-relevance items.

03

Configure & Launch

Choose your AI models, set query count, review token estimates, then launch all audits in one click.

04

Monitor Live Progress

Watch audits run in real time. Schedule recurring runs so you never miss a regression.

05

Review Consolidated Results

Get accuracy scores, hallucination flags, and judge reasoning across every model and every audit.

06

Deploy Fixes

Push remediation suggestions back to GitHub as a pull request, or download updated docs directly.

New Feature

AI discovers your endpoints automatically

Paste any GitHub repo URL. DocuTect scans your codebase for OpenAPI specs, route definitions, and documentation files, then uses AI to prioritise the most important items and mark them for audit — no manual entry required.

Detects REST routes, OpenAPI specs, and API definitions
Finds Markdown, RST, and TXT documentation files
AI ranks each item by audit relevance (high / medium / low)
Auto-selects high-priority items to save you time
Scan GitHub RepositoryAI-Powered
github.com/twilio/twilio-python
Scan
twilio/twilio-python — scanned 31 files, found 9 suggestions
highPOSTSend SMS Message
highGETList Messages
mediumPOSTCreate Phone Call
2 selected
Continue
New Document Validation
Search docs… (e.g. stripe, openai, fastapi)
AllREST APIAuthenticationWebhooksSDKs

Stripe Payments API

REST API

Popular

OpenAI Chat Completions

AI / LLM

Trending

Twilio SMS

Messaging

Upload your own .md / .rst / .txt

Documentation Hub

Validate your docs, not just your endpoints

DocuTect AI's Doc Hub audits technical documentation for accuracy, completeness, and consistency. Browse 500+ docs from the Context Hub registry, upload your own files, or scan your GitHub repo for documentation automatically.

500+ curated docs in the Context Hub registry
Upload .md, .rst, .txt files or a ZIP archive
AI scans GitHub repos and surfaces the right docs
Same hallucination detection and remediation engine as APIs
New Feature

From API docs to working integration code — in seconds

Scan any GitHub repo or documentation URL, pick your endpoints, optionally run an audit to correct inaccurate docs first, then generate production-ready integration code in 12 languages.

1

Provide source

GitHub repo or docs URL

2

Select endpoints

AI-ranked, checkbox selection

3

Audit (optional)

Fix inaccurate docs first

4

Pick language

12 languages supported

5

Review & confirm

See quota + cost before generating

6

Receive code

Copy and ship immediately

Audit-first means better code

Outdated or inaccurate API documentation produces incorrect integration code. With one toggle, DocuTect runs a full hallucination audit on the endpoints you selected before generating code — automatically applying remediations in memory so the generator works from corrected, verified content.

Scans GitHub repos or any documentation URL
Optional ~2 min/endpoint audit with Claude + GPT-4.1
12 languages: Python, TypeScript, Go, Java, C#, React, Rust, Kotlin, Swift, PHP, Ruby, JavaScript
Quota-gated: 10 free code gens + 3 free audits/month
Env-var safe — secrets never hard-coded in output
Step 2 — Select Endpoints
Found 12 endpointsSelect all
POSTCreate Charge/v1/charges
GETRetrieve Customer/v1/customers/{id}
POSTCreate Payment Intent/v1/payment_intents
GETList Invoices/v1/invoices
3 selected · $3 est.
Continue
Step 4 — Select Language
🐍Python
🔷TypeScript
🐹Go
Java
🟣C#
⚛️React
🦀Rust
🎯Kotlin
Step 6 — Results (Python) Generated
POST/v1/charges
GET/v1/customers/{id}
POST/v1/payment_intents
import stripe
import os

# Initialize Stripe client — use env vars, never hard-code keys
stripe.api_key = os.environ["STRIPE_SECRET_KEY"]

def create_charge(
    amount: int,           # Amount in cents (e.g. 2000 = $20.00)
    currency: str = "usd",
    source: str = None,    # Token from Stripe.js or card ID
    description: str = "",
) -> stripe.Charge:
    """Create a Stripe charge.
    
    Docs: https://stripe.com/docs/api/charges/create
    """
    return stripe.Charge.create(
        amount=amount,
        currency=currency,
        source=source,
        description=description,
    )
Ground Truth Bundle

One canonical source of truth — five tiers of evidence

Every audit compares LLM answers against a Ground Truth Bundle — 1 to 10 sources stitched together and weighted by trust tier. Higher-tier sources (OpenAPI specs, live API probes) override lower-tier ones (repo scans, manual notes) so findings reflect what your API actually does.

Tier A — OpenAPI spec by URL or pasted JSON (highest trust)
Tier B — Safe live probes (HEAD / OPTIONS / GET) verify endpoints exist
Tier D — GitHub repo scan infers routes from your code
Tier G — Manual reviewer notes for niche behaviour
Bundle: stripe-api-v15 sources · active
TIER Aopenapi.stripe.com/spec3.jsonOpenAPI URL
TIER Aopenapi-inline.jsonOpenAPI inline
TIER Bapi.stripe.com/v1/*Live probe
TIER Dstripe/stripe-nodeGitHub scan
TIER GRefunds idempotency noteManual
Bundle resolved · 142 endpoints indexed for comparison

Consolidated results across every audit

After your batch run completes, DocuTect assembles a single results view — accuracy scores, hallucination flags, and remediation actions for every endpoint and doc.

Batch Results — stripe/stripe-node · 5 audits

Completed: 5
Failed: 0
76%
Avg Accuracy
3
Hallucinations
5
Auto-fixable

Create Payment Intent

API Audit

POST
34%
Accuracy
critical

List Customers

API Audit

GET
91%
Accuracy
Clean

Create Refund

API Audit

POST
78%
Accuracy
medium

Authentication Guide

Doc Validation

85%
Accuracy
Clean

Webhooks Reference

Doc Validation

62%
Accuracy
low
Ready to deploy fixes
Create Pull Request

Compare every model, side by side

See exactly which LLMs get your API right — and which ones fabricate answers.

Model Leaderboard — Stripe Payments API

Ranked by accuracy. Trust badge combines accuracy and hallucination rate.

Trusted Mixed Risky
1
Claude 4 Sonnet
Anthropic
Accuracy
91%
Halluc.
8%
Trusted
2
GPT-4.1
OpenAI
Accuracy
83%
Halluc.
14%
Mixed
3
Gemini 2.5 Flash
Google
Accuracy
70%
Halluc.
28%
Risky
Scores computed by a third-party judge LLM — not self-reported
Recurring Audits

Catch regressions before your users do

Schedule audits to run automatically at any frequency. DocuTect recommends monthly re-runs to catch documentation drift as your API evolves.

dailyCatch regressions immediately on fast-moving APIs
weeklyBalance thoroughness with compute costs
monthly ★Recommended — catches drift before users notice
Auto-create PR when fixes are ready
Email me when each run completes
Audits running…
2 / 5 complete
Create Payment Intent
completed
List Customers
completed
Create Refund
running
Authentication Guide
pending
Webhooks Reference
pending
Monthly schedule active ★Next run: May 4, 2026
Simple, transparent pricing

Start free. Upgrade as you grow.

Free tier with 3 single audits per month. Premium at $100/month for 50 audits plus advanced features. Pay-as-you-go overages at $3 per audit.

Free

Perfect for getting started

$0

3 audits per month

Get Started

Features

3 audits per month
Single model testing
Basic remediation
Community support
Most Popular

Premium

For serious teams

$100/month

or $1000/year (17% off)

50 audits per month

Start Premium Trial

Features

50 audits per month
Single & batch audits
Multi-model testing
Advanced remediation
Priority support
Full API access
GitHub PR deployment
Team collaboration & invites

Overage audits

Create up to 5 audits beyond your limit. Each additional audit is $3 and billed at month-end.

Complete pipeline — from repo scan to GitHub PR

Find out what LLMs really say about your API

Connect your GitHub repo. AI discovers your endpoints and docs. Three models tested. Every hallucination exposed. Fixes deployed as a PR. Start in under a minute.