Engineering & DevTools
Internal Code Assistants.A code assistant that knows your codebase, not just Python.
Train a coding LLM on your internal repositories, architecture docs, coding standards, and proprietary SDKs. Get an assistant that suggests code following your conventions, understands your domain models. Train and run it on your own hardware and your code is not sent to an external API.
- Model weights, exportableYours
- Code sent to an external APINoneWhen you train and run on your own hardware.
- Train and run on your own hardwareSelf-host
The problem
GitHub Copilot and ChatGPT don't know your internal APIs, your monorepo structure, or your team's conventions. Worse, every code snippet you paste into them is potentially leaving your organization.
How Langtrain helps
Purpose-built for Engineering & DevTools.
Proprietary Code Stays Private
Fine-tune on your private repos with Langtune on your own hardware, and the model runs in your infrastructure. Your code does not leave it.
Knows Your Stack
Train on your internal monorepo, custom SDKs, and architecture decision records. Get suggestions that follow your conventions, not generic patterns.
IDE Integration
Call your fine-tuned model from the Python and Node SDKs or the REST API, from whatever editor and tooling your team already uses.
Compliance-Safe
For teams in fintech, healthcare, or defense where code cannot leave the building. Fine-tune on your own hardware with Langtune, so the code never leaves the building.
Onboarding Accelerator
New engineers ask the assistant questions about the codebase. It explains design decisions, suggests where to add features, and links to the right files.
Code Review Co-pilot
Integrate into your CI/CD pipeline. Flag potential issues, suggest tests, and enforce coding standards before PRs are merged.
Applications
What teams actually build.
- 01
Autocomplete with Private APIs
Fine-tune Starcoder or Codellama on your internal SDK. Get intelligent autocomplete that knows your `@company/core` package, not just npm.
- 02
Architecture Q&A
Ingest your ADRs, RFCs, and architecture diagrams. Engineers ask "why did we choose Kafka over RabbitMQ?" and get accurate, sourced answers.
- 03
Test Generation
Given a function, generate unit tests following your team's test patterns, fixture conventions, and coverage requirements.
- 04
Legacy Code Explanation
Point the assistant at legacy COBOL or undocumented Python. It explains what the code does, documents it, and suggests refactoring paths.
Check it first
Don't take our word for it. Test it on your own cases.
- 01
Hold back real cases
Keep 50 to 100 real examples out of the training data, with the answers you would accept.
- 02
Ask both models
Put the same questions to the base model and to your fine-tune, and read the answers side by side.
- 03
Have an expert review
Before anything ships, your engineers, in code review checks the answers and decides whether it is good enough.
How to run it: the quick start
No certifications yet: we have not completed a SOC 2 or ISO 27001 audit. For regulated data, train in your own environment.
Ready for Engineering & DevTools?Start with your own data.
Talk to us, or start fine-tuning on the free plan.