A team of AI agents
that lives in your repo.
It modernises your legacy code and burns down your backlog — under full human control.
The problem
Two jobs every org needs — and can never staff
These are the biggest "we know we need to, but never get to it" line items in engineering.
Modernise the legacy code
The 100k–150k-line app that works but rots: outdated frameworks, missing tests, security debt. Only seniors can safely touch it — and they're always busy.
Burn down the backlog
50 small bugs and chores piling up in Jira / Linear / GitHub. Each is individually trivial, collectively enormous, and nobody owns clearing them.
"I file a bug Monday, and it's fixed in three weeks." — every PM, everywhere.
Cost of inaction
Today's options all cost more than they look
Ignore it
Code decays, security debt accrues, small fixes take weeks. Delivery slows as senior capacity is consumed by toil.
Outsource it
Premium consultancy rates, no knowledge of your conventions, and the expertise walks out the door at contract end.
Hire around it
Junior engineers: slow ramp, high fully-loaded cost, and the technical-debt backlog still never gets prioritised.
The solution
Governed AI engineering, inside your repo
CortexBuild reframes both jobs as incremental, auditable work — measured in PRs you approve, at a cost you can see line-by-line.
You stay in control
Approval gates at every step. Nothing irreversible without your yes.
Your keys, your code
Bring your own LLM keys. Data and spend never leave your hands.
Best practices baked in
Security review, audit trails, and conformance scoring come standard.
It lives in your repo
Agents work in git, through your real backlog — IDE untouched.
The model is a commodity; the harness is the moat. CortexBuild is that harness — a rendered control loop (the fully autonomous orchestrator is on the roadmap), governance rendered to every agent surface, deterministic eval gates, and a recurrence-ledger feedback loop — so you adopt the next frontier model on your own keys without rewriting what keeps its output safe to ship.
How it works
Five steps from connect to merged
The differentiator
A team of agents, not a lone bot
Specialised agents run in a disciplined sequence — the way a mature engineering org works.
The roster
Ten specialised agents
Each runs on the right model tier — premium reasoning where it counts, cheap tokens everywhere else.
Governance
Planned approval matrix: 20 action classes × 3 levels
Roadmap — Phase 2. You configure the autonomy ceiling per project. Nothing irreversible runs without explicit approval.
| Level | Behaviour | Example actions |
|---|---|---|
| AUTO | Performed silently; visible in audit log | Read code · create branch · edit files · open PR |
| NOTIFY | Performed with a banner; rollback within 5 min | Install dependency · modify CI · merge to staging |
| APPROVE | Blocking dialog; agent waits for explicit yes / no | Merge to main · deploy to production · spend money · rotate secrets |
Shift any row toward more control or more autonomy. Going below the recommended default needs a confirmation dialog — and is audit-logged.
Use cases · Surface A
Legacy modernisation
Onboard & map a 150k-LOC repo
Connect in < 5 min, analyse in < 30 min, and get a ranked roadmap of 15–30 issues with a tech-debt heatmap — to edit, not accept blindly.
Confirm conventions before enforcing
Inferred rules arrive with 3–5 file:line citations. Choose Enforce / Advisory / Discard. Your decision is remembered.
Approve a roadmap in plain English
Business-impact summary, effort, risk, and blocker chain per issue. Drag-reorder, tag by quarter — no code required to govern.
Review a PR in 5 minutes, not 30
Structured body: plan, pre-mortem, evidence, rollback, confidence score. Low confidence opens as a draft.
Use cases · Surface B & cross-cutting
Backlog burn-down & trust
Triage & auto-clear
Triage 50 tickets in < 5 min (complexity, confidence, action). Work S-tickets above the 0.85 confidence floor in parallel; PRs open as they finish.
Plan-then-execute on medium tickets
A plan (API · DB · frontend · tests · pre-mortem) with a Critic review, approved before code exists.
Rollback & learn
One-click revert + post-mortem → recurrence-ledger entry → Critic gate blocks that failure class forever.
OOO approval delegation
The approval queue is project-level: any admin can decide, attributed in the audit log. Work is never blocked by one calendar.
Who it's for
Built for both sides of the table
Priya — Product Manager
- Plain-English roadmaps — prioritise by business impact, no diffs
- Cost dashboard to defend spend to the CFO — real-time, per-task, CSV export
- Audit log for compliance — every action attributable
- "What's shipping this week?" answered without interrupting engineering
Devansh — Staff Engineer
- Delegate dependency upgrades, test backfilling, and docs
- Every PR arrives with plan, evidence, and rollback notes
- Relax autonomy as trust grows — the matrix is editable any time
- Recurrence ledger makes the agents smarter with your codebase
ROI model · worked example
Transparent, conservative, your numbers
40 tickets/mo · $90/hr · 3 hrs/ticket · 50% autonomous · $0.40/ticket (BYO key)
Estimate. Actual results vary by codebase, ticket mix, and configuration. LLM tokens are billed directly to your own provider keys — ~0.15% of gross savings here.
ROI · sensitivity
Net savings per month
Net per autonomous ticket = 3 × $90 − $0.40 = $269.60.
| Autonomous share | 20 tickets / mo | 40 tickets / mo | 80 tickets / mo |
|---|---|---|---|
| 30% | $1,618 | $3,235 | $6,470 |
| 50% | $2,696 | $5,392 | $10,784 |
| 70% | $3,774 | $7,549 | $15,098 |
AI optimization
Current best practices, automatically
Per-action model routing
reasoning_heavy · balanced · fast_cheap — premium tokens only where reasoning is needed.
BYO-key, no lock-in
Claude · Copilot · Codex · Bedrock · Vertex · Ollama. Bedrock/Vertex via OpenAI-compatible gateway. Data stays in your keys and sandbox.
Self-learning ledger
Every failure becomes a permanent guard. The system compounds across projects.
Rule SSoT
One governance source renders to Copilot, Claude, Cursor, and Codex — no drift.
Confidence thresholds
Autonomous PRs need a configurable floor (default 0.85); low confidence → draft.
Adversarial Critic + self-audit
A second model challenges the plan; every agent self-audits before completion.
As providers and best practices evolve, CortexBuild's routing, rules, and guardrails carry your team forward — no re-training required.
Enterprise standards
Secure, isolated, auditable
- BYO keys — KMS-encrypted, never leave the control plane
- Per-project sandbox — Daytona-based, self-hostable (planned, Phase 1)
- Tenant isolation across every action
- Full audit log — actor, action, target, payload, timestamp; hash-chained
- Retention tiers — 90 days · 1 year · 7 years (enterprise)
- PII classification — geo / identity / biometric tagged & gated
- RBAC with a single permission registry
- Approval matrix — 20 classes × 3 levels
- Standards — OWASP ASVS · NIST SSDF · ISO 27001-aligned · WCAG 2.2 AA
- Conformance score — deterministic, anti-gaming 0–100
The conformance score is recomputed from primary evidence on every run — hand-editing the report has no effect. Absence of evidence scores zero.
Why us
The empty quadrant: multi-agent + governance
| Capability | Single-agent tools | CortexBuild |
|---|---|---|
| Agent model | Single agent | Multi-agent wave + adversarial Critic |
| Governance | "Yolo" mode or none | 20-class approval matrix + full audit |
| Learning | Forgets each session | Recurrence ledger — compounding memory |
| LLM provider | Often vendor-locked | BYO key — six providers |
| Policy consistency | Per-tool prompts | Rule SSoT — render once, fan out |
| Audience | Single developer | PMs and tech leads |
Moats: Rule SSoT (hard to retrofit) · recurrence ledger (network effect) · brownfield analyser · BYO-key from day one · fine-grained approval matrix.
Pricing
Start free; pay for the hosted control plane
Individuals and teams running the engine on their own hardware.
Hosted UI + control plane. Each seat manages a team of agents — same headline price as single-seat assistants.
Tenant isolation, long retention, security review, and support agreements.
You pay LLM tokens directly to your provider. CortexBuild does not mark up usage.
Start a 30-day pilot.
Measure the savings.
Owned, not outsourced. Your repo, your keys, your approval gates.