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 write code.
The software factory delivers production-ready changes.
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.
Platform
Three capabilities around every agent-built change.
It connects the context agents need, the owners who need to coordinate, and the evidence reviewers need before release.
Organizational Memory and Product Understanding
Product Behavior, Customer Impact, Workflows, Repositories, Owners, Contracts, Infra, Decisions, Incidents, Rollout History, plus facts and relationships learned from every run.
Outcome Delivery
Specialist agents coordinate Product requirements, Frontend, Backend, Workers, Infra, Verification, and Rollout from one requested outcome.
Verified Changes
Tests, 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
Product Requirements, 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.
Why a Software Factory
Coding agents are workers. The factory is the delivery system.
Codex, Claude, Cursor, and Custom Agents can produce code quickly. The Software Factory adds the organizational layer that makes the change coordinated, verified, and ready for review.
Coding Agents Alone
Software Factory
Engineering Context
Works from the repo, prompt, and visible files in the current session.
Uses Organizational Memory: Product Behavior, Customer Impact, Owners, Contracts, Infra, Incidents, Decisions, and Rollout History.
Cross-Repo Work
Creates local changes, but dependencies across Product behavior, Frontend, Backend, Workers, and Infra still need manual coordination.
Coordinates the Outcome: Product Requirements, affected repos, compatible contracts, sequencing, owners, and release order.
Verification
May run local tests, but integration proof, screenshots, logs, and contract results are usually assembled by engineers.
Packages Evidence: Tests, logs, screenshots, contract checks, review notes, and PR summary in one place.
Rollout Readiness
The deploy order, monitors, rollback path, and release risk still live in team knowledge.
Plans the Release Path: Rollout order, monitors, rollback path, and reviewer-ready decision context.
Learning
Each session can start fresh unless a human carries forward what failed last time.
Improves Every Run: New facts update memory, repeated manual work becomes workflow, and failed checks become gates.
Operating Model
Everything your agent doesn't know before it ships.
01
Remember
Recall the Product Behavior, Customer Impact, Workflows, Repositories, Owners, Contracts, Infra, Incidents, Decisions, and Release Constraints that matter.
ok owners mapped
ok contracts loaded
02
Coordinate
Bring Product requirements, Frontend, Backend, Worker, Infra, Verification, and Release work together around the outcome.
ok 4 repos sequenced
ok owners aligned
03
Verify
Run tests, contract checks, logs, screenshots, migrations, monitors, and integration flows.
ok 22 checks packaged
ok rollback path set
04
Learn
Capture two kinds of learning: facts for Organizational Memory and improvements to workflows, skills, gates, and agents.
new facts stored
new workflow improved
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 Product, Frontend, Backend, Worker, and Infra.
The Product Behavior is mapped first, the API expands safely, 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.
CodexAI Coding Agent
ClaudeAI Coding Agent
CursorAI Coding Agent
Custom AgentsAny Agent via API
GitHubRepos, PRs, CI
LinearIssues and Planning
SlackTeam Coordination
DatadogLogs, Metrics, Traces
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, Infrastructure, 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.
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.