Real tasks from
real codebases for AI training

We generate high-quality, exclusive software engineering tasks from private production codebases — bug fixes, refactoring, test generation, PR reviews, and more. Purpose-built datasets for training and evaluating the next generation of AI coding models.

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7 task types from real codebases

We source private production codebases and generate diverse software engineering tasks across 7 categories. Every task comes from real code written by real engineers — no synthetic or toy examples.

Each task includes full repository context, clear instructions, and verification criteria. These datasets are built specifically for training and evaluating AI coding models on the work that software engineers actually do.

Bug Fix

Real bug reports paired with verified fixes from production codebases. Each task includes the issue context, failing tests, and the correct patch.

CI/CD

Pipeline configuration, build system fixes, and deployment workflow tasks sourced from real continuous integration and delivery setups.

Decision

Architectural and design decision tasks where the model must reason about trade-offs, choose approaches, and justify engineering choices.

Multi-file Reasoning

Tasks that require understanding dependencies across multiple files and modules — navigating large codebases to produce coherent changes.

PR Review

Code review tasks where the model must analyze pull requests, identify issues, suggest improvements, and provide actionable feedback.

Refactoring

Code restructuring tasks that improve maintainability, performance, or readability while preserving existing behavior and passing all tests.

Test Generation

Tasks requiring the model to write meaningful test cases that cover edge cases, improve coverage, and validate existing functionality.

Why your model needs private codebase tasks

The best AI coding models are trained on exclusive data that reflects real engineering work. Public benchmarks are saturated — exclusive, private codebase tasks are the next frontier for model improvement.

1

Exclusive data, zero contamination

Public repos are already in every model's training data. Our exclusive tasks come from private production codebases that have never been scraped — data your competitors don't have. Your model learns genuinely new patterns rather than memorizing known solutions.

2

Production-grade complexity

Real engineering challenges from active codebases with complex dependencies, legacy code, and cross-cutting concerns. These tasks reflect the difficulty of actual software work, not sanitized textbook problems.

3

Diverse task coverage

Seven distinct task types — from bug fixes to PR reviews to architectural decisions — train models across the full spectrum of software engineering work, not just code generation.

4

Verified and executable

Every task comes with test suites and verification criteria. Models trained on verified tasks learn to produce code that works, not code that merely looks plausible.

What you get

High-quality training data built from real software engineering work. Every task is sourced, verified, and packaged for model training and evaluation at scale.

Curated private repositories

1,000+ production-grade codebases with real contributors, pull requests, and engineering practices. 90+ days minimum activity history. Zero synthetic code.

Multilingual coverage

Tasks generated across Python, Java, JavaScript, TypeScript, Go, Rust, C++, C#, Ruby, PHP, and Swift — covering the languages that matter for real-world AI coding tools.

Full context per task

Every task ships with the complete repository snapshot, issue description, relevant file context, and test suites. Everything a model needs to learn end-to-end.

Contamination-free

Tasks are sourced from private codebases and filtered by creation date relative to model training cutoffs. No overlap with public training corpora.

Continuously growing

Fresh tasks ingested from active codebases on an ongoing basis. New pull requests and issues become new training data, keeping your dataset current.

Scalable generation

Our SWE-Bench++ framework can generate thousands of execution-based tasks on demand. Scale your training data without compromising quality.

How we can help

We are Bhavitech. We provide exclusive tasks and codebases to companies training AI coding models. Whether you need ready-made datasets or custom task generation from private codebases, we deliver exclusive, production-grade training data at scale.

Exclusive task datasets

Pre-built exclusive datasets of 11,000+ execution-based tasks across 7 categories and 11 languages. Data that isn't available anywhere else — ready to integrate into your training pipeline.

Custom codebase sourcing

We source and curate private codebases tailored to your model's target domain — fintech, healthcare, devtools, infrastructure, and more.

Custom task generation

Need tasks focused on a specific language, framework, or task type? We generate custom datasets to match your training objectives.

Evaluation benchmarks

Use our contamination-free task sets as private benchmarks to measure your model's real capabilities — beyond what public leaderboards show.

Contact us

Interested in improving your AI's SWE-bench performance or building a coding agent? Let's talk.