Bhavitech sources real-world codebases, JIRA exports, Slack threads, and Figma files — with the relationships between them intact. Built for fine-tuning, evals, and benchmarks.
Trusted by teams building frontier models
Most data vendors sell isolated files. Bhavitech sells the relationships: a commit linked to its JIRA ticket, linked to the Slack thread where it was discussed, linked to the postmortem if something broke.
This is what makes evals and fine-tuning more realistic — models trained on connected artifacts understand how real engineering decisions flow across tools.
commit a1b2c3d fix: payment retry logic
├── jira PROJ-1234 Payment timeout bug
├── slack #backend "retry should cap at 3"
├── figma Payment Flow v2
└── postmortem 2024-01-15 incidentSix categories of engineering artifacts, delivered with metadata and clear licensing.
Production repositories with real contributors, commit history, PRs, and branching patterns. Not toy projects.
Tickets, epics, sprints, and comments. See how engineering teams plan, prioritize, and track work.
Engineering discussions, architecture debates, and decision threads. The context that never makes it into code.
Design-to-implementation artifacts. See how visual decisions translate into engineering requirements.
Business and product requirement documents. Understand the 'why' behind engineering decisions.
Incident reports and resolution threads. How teams debug, recover, and prevent recurrence.
Training models on realistic, multi-file engineering tasks
Building evals that test real-world reasoning, not just code completion
Improving code assistants with authentic engineering workflows
Studying how models handle complex, multi-step engineering decisions
Stack, domain, artifact type, volume, quality bar
Programmatic checks + human review against your spec
Metadata, clear licensing, and secure transfer
Get sample datasets delivered within days.