TACO is a software change management platform that removes your engineering backlog — without adding headcount. On-premises. Human-approved. Works with your existing tools.
Every software team hits it. More requirements than hands. Backlog growing faster than delivery.
Senior engineers write boilerplate instead of architecture. Product managers wait 2 sprints for a label change. The bottleneck is not ideas — it is hands.
Only the original developer truly understands the codebase. When they're busy — or gone — everything slows down. Every new hire starts from zero.
No clear approval trail. No automated tests on every change. Every deployment is a fingers-crossed moment. Production incidents trace back to untested changes.
"TACO removes that bottleneck without adding headcount."
Same team. Same codebase. Dramatically higher output — with human approval at every step.A governed, traceable lifecycle for every change — from plain English description to production.
Anyone describes what they need in plain English. Or it arrives automatically from Azure DevOps, Freshdesk, ServiceNow, or SaraDesk via the ingest API.
TACO scans your repository using tree-sitter. Understands structure across 40+ languages. Finds the relevant files in <100ms using vector search — without sending your full codebase anywhere.
Which files to change, what exactly, and what the impact will be. A complete, human-readable implementation plan is generated and presented for review before any code is written.
Engineering lead reviews and approves from the web dashboard or mobile PWA. Installable on iOS and Android. Approve or reject from anywhere — nothing proceeds without sign-off.
Code is written and pushed to the developer's machine via the lightweight TACO Agent — a background process that writes files to the local repo and notifies via desktop notification.
Playwright tests execute against the change. Results appear directly in the dashboard. Failures block progression — quality is built in, not bolted on.
On test pass and UAT approval, TACO triggers your existing pipeline. Use the webhook you already have. TACO connects to it — it does not replace it.
Not a code autocomplete. Not a cloud AI service. A governed AI change management platform where CTOs see the big picture, BAs feed in requirements, and developers ship safely.
PHP from 2008, Java microservices, React TypeScript, .NET Framework, Swift, Python — TACO reads all of them using tree-sitter. Legacy codebases included.
Runs entirely on your company servers. Zero cloud dependency. No code sent to external AI services without your explicit configuration. On-premises by design.
AI plans and drafts. Humans decide. The plan must be approved before coding begins. Tests must pass before CI/CD fires. Nothing ships without sign-off.
CTOs and Delivery Heads get a live governance dashboard — velocity by week, AI spend per project, policy compliance score, risk distribution, and active agent status. Zero technical knowledge required.
See exactly what your AI coding spend is — per developer, per project, per task. Set monthly budgets. Hard-stop enforcement before the limit is hit. No more surprise cloud bills.
Business Analysts upload requirement documents (PDF, Word, Markdown). TACO extracts them into structured context. The AI reads your actual specs when writing code — not guesses.
TACO's frontend is a Progressive Web App. Installable on iOS and Android. Engineering leads can review AI plans and approve changes from anywhere, anytime.
REST ingest API accepts tickets from Azure DevOps, Freshdesk, ServiceNow, and SaraDesk. Per-project API keys. Bi-directional sync configurable per integration.
A lightweight background process on each developer's machine. Receives AI-generated code via WebSocket, writes files to the local repo, and reports status back — fully automated.
Most AI coding tools serve developers and ignore everyone else. TACO gives every stakeholder — from the CTO to the BA — exactly what they need.
"I have no idea what our AI tools are actually doing or what they're costing us each month."
Live KPI Board. Weekly velocity, AI spend by project, policy compliance score, risk breakdown, and active agents — in one executive screen. No login to Jira. No Slack digging.
Reviews every PR while drowning in context-switching. Never knows what the AI actually sent to the LLM, or what it'll cost.
Structured approval gate — AI presents the exact plan before coding. Policy engine blocks unsafe changes automatically. Token cost attributed to every task. Full audit trail in one click.
Waits 2 sprints for a label change. Writes tickets that developers then have to decode before the AI can act on them.
Describe the change in plain English. Review the AI plan. Click approve. Code ships — in hours, not sprints. No translation required.
"I wrote a 40-page requirements document. The developer explained it to the AI. The AI still got it wrong."
Upload your requirements doc to the project. TACO's AI reads it directly — no re-explanation. Every task planned against your actual spec. Traceability from requirement to code.
Writes boilerplate all day. Uses AI tools but they hallucinate — and nobody catches it until the PR review.
TACO agent runs locally. Receives AI-generated code, writes it to your repo, runs tests. You review the output — not raw AI. Policy engine catches dangerous patterns before they land.
Receives code with no context on what changed, why, or what risk it carries. Regression scope is always unclear.
Every task has a full AI plan — which files changed, what the intent was, what risk level the policy engine assigned. QA knows exactly where to focus. Tests run automatically before sign-off.
Plug TACO into the tools your team already uses — via a simple REST ingest API with per-project API keys.
Also works as a fully standalone platform — no external system required.
A distributed architecture purpose-built for on-premises deployment. AI on the server. Code application on each developer's machine.
React PWA frontend, FastAPI backend, TACO AI Engine (planning + code generation using Claude), PostgreSQL with pgvector, Redis, and Celery workers. All AI computation happens here — your code stays in your infrastructure.
A lightweight Python background process. Connects to the server via WebSocket, receives generated file contents, writes them to the local repo, shows desktop notifications, and reports status back. Cross-platform: Mac, Windows, Linux.
Key principle: AI planning and code generation run on the backend server. Only file application happens on developer machines via the TACO Agent. No code leaves your corporate network.
The questions every engineering leader asks before evaluating TACO.
Book a free 45-minute discovery call. We'll map TACO to your exact codebase, team size, and existing tools — no generic demo, no commitment.