Context is missing
Agents need architecture, ownership, service contracts, customer impact, infra, decisions, and rollout history before they can make the right change.
Engineering brain for software factories
Your agents ship code.
The software factory proves it belongs in production.
Prinevo gives engineering teams a software factory around coding agents: organizational memory, coordinated repo changes, sandbox verification, rollout planning, and a PR package reviewers can trust.
Built for engineering teams using Codex, Claude, Cursor, and custom agents across multi-repo systems.
Organizational memoryProduct flows, customer impact, repositories, owners, contracts, infra, decisions, incidents, rollout history, plus facts and relationships learned from every run.
Outcome deliverySpecialist agents coordinate implementation, verification, and rollout from one requested outcome.
Verified changesTests, logs, screenshots, contract results, and reports packaged for review.
The delivery gap
Agents speed up code. Teams still have to make it shippable.
Today, senior engineers still supply the missing system context, coordinate the work across repos and teams, and assemble the proof reviewers need before release.
Coordination is the bottleneck
Frontend, backend, workers, infra, tests, reviews, and deployment order still have to line up across teams and repositories.
Trust has to be earned
Engineering teams still assemble the proof manually: code review signals, test results, logs, screenshots, monitors, rollback path, and PR context.
Operating model
From one requested outcome to a verified software change.
The factory chooses the right path. Small fixes stay lightweight. Cross-repo, API, infra, data, and rollout-sensitive work gets coordinated delivery, sandbox verification, review-ready output, and lessons that shape the next run.
Remember
Recall the product flows, customer impact, repositories, owners, contracts, infra, incidents, decisions, and release constraints that matter.
Coordinate
Bring frontend, backend, worker, infra, verification, and release work together around the outcome.
Verify
Run tests, contract checks, logs, screenshots, migrations, monitors, and integration flows.
Learn
Capture two kinds of learning: facts for organizational memory and improvements to workflows, skills, gates, and agents.
Delivery package
Ask for the outcome. Get coordinated changes, checks, and a rollout path.
Map the affected repos, owners, contracts, and deployment order.
The factory retrieves organizational memory: why similar changes failed, which constraints blocked deployment, and which checks proved the path last time.
Coordinate compatible changes across the system.
The API expands first, the worker emits the new event, and the frontend consumes it behind a rollout flag.
Package reviewer-ready output.
Test reports, runtime logs, screenshots, contract notes, rollout order, monitors, rollback path, and new memory facts are packaged with the PR.
Integrations
Connect the systems where delivery context already lives.
Connect GitHub, GitLab, Linear, Jira, Slack, Notion, Google Drive, CI, cloud, observability, incident management, and deployment systems so the agent fleet works from the same engineering context your team already uses.
Planning and docs
Product intent, decisions, specs, ownership, review notes, and architecture records.
Code and runtime
Repos, PRs, CI, deployments, cloud config, logs, metrics, traces, and incidents.
Operational memory
Deployment blockers, failed setups, repeated manual checks, rollout lessons, and verification playbooks.
Beyond code changes
Once the factory has context, it can support the rest of engineering.
Cost, reliability, security, and compliance issues all connect back to code, infra, ownership, runtime behavior, deployment history, and customer impact.
Example investigation
Why did data warehouse costs spike last month?
Signal
Cost increased 28% after the analytics worker deployment.
Trace
Correlate spend, deployments, logs, traces, and query metrics to one repository, module, and path.
Action
Find the root cause, estimate savings, make the code change, and open a PR with the supporting signals.
Production-ready code changes
Produce architecture notes, coordinated repo changes, review signals, test evidence, rollout plan, and a PR ready for deployment.
Cost analysis
Connect cloud spend, deploy history, metrics, queries, workers, repos, and owners.
Reliability diagnosis
Trace incidents to code paths, rollouts, monitors, service contracts, and regression tests.
Security and compliance
Review changes against data flows, policies, audit needs, ownership, and release readiness.
Production debugging
Use logs, traces, infra config, docs, incidents, and repo context in one investigation.
Private pilot
Evaluate Prinevo on real engineering outcomes.
Early access is for engineering teams using coding agents in production workflows. Bring a multi-repo change, verification flow, or rollout package you want to make trustworthy.