Engineering outsourcing · rebuilt for agents
Senior engineers.
Fleets of AI agents.
Every merge signed.
Apex Fleet is an engineering outsourcing firm. We staff your product with proven senior engineers, each commanding a dedicated fleet of AI coding agents on dedicated machines, and with the product, QA and DevOps people to run the whole cycle. One engineer or a whole team. A team's output at a fraction of the headcount, with a named human on every merge.
Runs on Claude Code or OpenAI Codex, whichever your security team approved.
30 minutes with the engineer who'd run your fleet. Written quote within two business days.
- Senior engineers, 10+ yrs each
- A dedicated agent fleet per engineer
- Every change reviewed and merged by a named engineer
- Teams of 1 to N · Proving Sprint · 30-day exit
review · merge
What we take on
Five kinds of work. One way of shipping it.
Every engagement runs the same way: in your repo, through your CI and PR process, with a named engineer on every merge. What changes is what the fleet is pointed at.
Build a product from zero to v1
For a funded idea that needs a real product, not a prototype. The engineer owns architecture and the parts that must be right the first time; the fleet builds the surface area in parallel.
- Agents
- scaffolding · CRUD and admin · integrations · tests · docs
- Engineer
- architecture · data model · auth, billing, migrations by hand · every merge
- Example scope
- Multi-tenant SaaS: SSO, Stripe billing, admin, CI/CD with gates, first production deploy.
Throughput for a live product
Your roadmap is longer than your team. A unit takes a delegated slice of the backlog and ships it through your own PR process, without burying your reviewers.
- Agents
- feature tickets · bug backlog · test backfill · refactors under 300 lines
- Engineer
- decomposition · review of every diff · ADRs · your standups and design reviews
- Example scope
- A quarter of feature tickets for one product area, plus the test coverage nobody had time for.
Legacy modernization and migrations
Framework upgrades, monolith carve-outs, language and runtime migrations. Fleets are good at wide, mechanical change; the engineer keeps it behaviour-preserving and proves it.
- Agents
- characterization tests · module-by-module migration · dependency upgrades
- Engineer
- migration strategy · equivalence proof · cutover plan · rollback
- Example scope
- Node 16 to 22 and Express to NestJS across 40 services, one reviewed PR per service.
Platform, infrastructure and DevOps
CI/CD, infrastructure as code, observability, cost. Runbooks written as code and left in your repo, so your team can run it without us.
- Agents
- Terraform and Helm · pipelines · dashboards and alerts · runbooks
- Engineer
- topology · security boundaries · production changes by hand · cost review
- Example scope
- Kubernetes on GCP or AWS, Terraform, CI with gates, on-call runbooks, monthly cost report.
AI features inside your product
LLM features, agents, retrieval, voice. We run agent fleets for a living and know where they break: evals first, cost ceilings before scale, failure modes written down.
- Agents
- eval harnesses · tool and prompt scaffolding · integration code · fixtures
- Engineer
- eval design · guardrails · cost gates · what the model is never allowed to do
- Example scope
- Voice agent wired into a CRM, with evals, transcripts, and a cost ceiling per call.
The shift
Speed is now cheap. Ownership isn't.
AI writes most new code now. The scarce resource is a senior human who can tell right from almost-right — and is accountable for the difference.
Google's DORA research calls AI an amplifier: it magnifies the discipline a team already has — or the lack of it. We staff the bottleneck that finding points at: one accountable senior engineer at the merge.
The model, Monday to Friday
How a fleet week works
1 Fleet Unit = 1 staff engineer (10+ years) + their dedicated fleet of coding agents + the machines and model usage they run on. One human, N agents in parallel, one merge line. Here is what that unit does in a week.
Decompose
Your engineer breaks the agreed backlog slice into small, independently testable units: a PR under roughly 300 changed lines, acceptance test specified first. Auth, crypto, payments and migrations are flagged for engineer-written work, never default fleet dispatch.
Dispatch
Each unit goes to one agent on the engineer's dedicated machines: one worktree per agent, one branch per unit, typically four to eight agents in flight. Agents run with your repo's conventions loaded, written by the engineer in week one and committed to your repo.
Gate
Every branch passes your CI plus ours before a human reads it: tests, lint, type checks, SAST, secret scanning, licence scanning. Any diff that deletes, skips or loosens a test is blocked automatically.
Review
The engineer reads every diff that clears the gates. Not skims — reads. Duplicated helpers, masked errors and misread requirements go back to the fleet. A fleet that never gets rejected isn't being reviewed.
Merge
Only the engineer merges, into your repo, through your PR process and CODEOWNERS. Every PR states what was agent-authored and what the engineer changed by hand. If your review queue backs up, we throttle dispatch.
Report
Friday: a one-page fleet report. What merged, what was rejected and why, what's in flight, CI pass rate, review turnaround for your team, and architecture decisions recorded as ADRs in your repo.
The whole cycle
Not just the code. The whole road to production.
Product, delivery, engineering, QA and DevOps. Every discipline runs on the same rule: a named human owns the decisions and signs the output, a fleet does the volume, and the artefact lands in your repo and your tools, not ours.
Discover and define
- Fleet does
- market and competitor scans · interview synthesis · PRD and spec drafts · analytics queries
- Human signs
- the problem · the priorities · the PRD
- Lands in
- docs/prd/ · your roadmap tool
Plan and run the week
- Fleet does
- backlog decomposition drafts · status and risk reports · estimates against your history
- Human signs
- scope · sequence · the weekly commitment · one point of contact
- Lands in
- your Jira or Linear · fleet-report.md every Friday
Build
- Fleet does
- implementation in parallel · tests · docs · small reviewed PRs
- Human signs
- architecture · every diff · every merge
- Lands in
- your repo, behind your CI · ADRs in docs/adr/
Verify
- Fleet does
- test generation · e2e suites · regression runs · exploratory checklists
- Human signs
- test strategy · acceptance · release readiness
- Lands in
- tests/ · e2e in CI · a release checklist
Ship and run
- Fleet does
- infrastructure as code · pipelines · dashboards and alerts · runbooks
- Human signs
- every production change · the release · the on-call hand-off
- Lands in
- infra/ · .ci/ · runbooks/
Every role is a unit. One named human plus their fleet, priced the same way as an engineering unit. Most engagements start with engineering and add QA and DevOps as the fleet scales; product and delivery units join for a build from zero or a programme with a deadline.
compose them into a team ↓Team shapes
One unit, or a team built from them.
The Fleet Unit is the building block. Teams are composed of units, one merge line each, and priced the same way. Scale by adding a unit, not a body.
Fleet Unit
1 engineer · 1 fleetOne senior engineer and their dedicated fleet. Joins your team, takes a delegated slice, owns every merge in it.
- 1 staff engineer, 10+ yrs
- 4–8 agents on dedicated machines
- weekly fleet report
Squad
2–3 units · 1 leadTwo or three units, one of the engineers as lead. One architecture, one merge line, one Friday report across all of them.
- lead owns architecture and ADRs
- each unit owns its track's merges
- every engineer named and interviewed
Delivery team
PM · lead · 3–6 eng units · QA · DevOpsA delivery manager runs the week. A lead unit owns architecture and the merge line. Units take tracks. QA and DevOps units own the gates, pipelines and releases. A product unit when the roadmap needs one.
- delivery manager is your single point of contact
- QA and DevOps units own gates and releases
- hand-off deliverable per track
Same rules at every size. Each unit is a named engineer you interview before signing. Each fleet is sized to what that engineer can genuinely read. Add a unit when you need more; remove one on 30 days' notice. Nothing merges without a human's name on it.
priced per unit per month · lead included · see pricing ↓Why quality holds
One name on every merge. Not "the AI".
Nothing reaches your main branch unless all of this is true.
Small enough to read in one sitting
Target under roughly 300 changed lines. Larger changes are split before dispatch, not after.
Your CI is green, plus our gates
Unit and integration tests, lint and type checks, SAST, secret scanning, open-source licence scanning. Gate configuration lives in your repo, in the open.
Tests were not weakened
Any diff that deletes, skips or loosens a test is blocked automatically and needs a written justification from the engineer. Agents may add tests. They may never remove one.
The engineer read the full diff
Agent code gets the same standard as a new hire's first PR, because the failure mode is the same: clean-looking, consistently styled, and almost right.
Security-sensitive paths got a second read
Auth, authorization, cryptography, input validation, payments and migrations never get the fleet's default speed. Veracode's 2026 benchmark found AI-generated code introduced a security flaw in roughly 44% of tasks, unchanged from the year before.[6]
The audit trail is your git history
Every PR records task, model, gates passed, reviewer and disposition. If code the engineer merged is in an incident, they are in the incident review. If we disappear, the trail stays.
Add rate limiting to /v2/orders #214
Audit trail
- What agents can never do here
- Merge
- Touch production
- Edit or delete a test
Versus the alternatives
Four ways to get more shipped. Three of them bill you for the wrong thing.
We are an outsourcing firm, so we know the model's failure modes from the inside. Here is what we changed.
Traditional outsourcing bills you for hours and heads
Blended rates, long minimums, buyout fees. The senior you met in sales is often swapped for someone cheaper by week six. You rent time; nobody owns the merge.
Freelancers give you one pair of hands
Good for one person's output. No fleet, no continuity, and no one on the hook when it breaks at 2 a.m.
In-house hiring gives you a wait
The right answer for your core, and roughly 65–75 days to fill a senior seat, then months of ramp.[11] Then you still have to teach them to command agents.
AI tools give you a licence
Tool-only adoption measured roughly 10–15% productivity gains; redesigning the whole workflow around AI measured 25–30%.[10] Agents without orchestration and review discipline produce more code, more churn and more unreviewed merges.
| Traditional outsourcing | Freelancers | In-house hire | AI tools alone | Apex Fleet · outsourcing, rebuilt | |
|---|---|---|---|---|---|
| Who is accountable for each merge | Whoever is on the ticket; often rotated | The freelancer, until the contract ends | Your team, once ramped | Nobody, unless you staff the review | One named staff engineer, written into the SOW |
| What you pay for | Hours or seats at blended rates | Hours | Salary, recruiting and ramp, plus agent spend | Licences and tokens; review unpaid | One Fleet Unit per month: engineer, machines, model usage |
| Time to first merged PR | Weeks to place, then ramp | Days, at one person's pace | ~65–75 days to fill, months to ramp [11] | Instant, then a months-long learning curve | Inside the first week |
| How speed scales | Add people and hours | It doesn't | Hire more | By volume; your review queue grows with it | Parallel agents behind one reviewer; add a unit for more |
| What happens to quality at speed | Review lands back on your team | Depends entirely on the person | Holds, once they've learned to run agents | More bugs, more churn, more unreviewed merges [2] | Every change gated by tests and read by the engineer; rejection rate reported weekly |
| Who reviews the AI output | Often nobody senior | The freelancer, if at all | Your seniors, the ones already overloaded | Your seniors, again | The named engineer, before your team ever sees it |
| What you keep when it ends | The code; the know-how leaves | The code; the know-how leaves | Everything, if they stay | Configs, if anyone wrote them | Everything: code, tests, ADRs, agent configs, runbooks, in your repo from day one |
| Exit terms | Long minimums; buyout fees common | Whenever they go quiet | Notice periods and severance | Cancel the licence; keep the debt | Proving Sprint first; then 30 days' notice, either direction |
Built for funded startups and mid-size product teams that need a team's output without a team's headcount, and want to keep core architecture in-house. First merge inside the first week. Every merge signed. Everything the fleet learns lives in your repo.
Security, IP and stack
Your repo. Your keys. Your stack.
Written so your security lead can say yes without a call.
Dedicated machines per engagement
Your fleet's boxes run only your work. No shared tenancy across clients; decommissioned at engagement end, with the wipe confirmed to you in writing.
Zero-retention endpoints, or your own agreement
Model traffic runs under zero-data-retention, no-training terms by default, or under your own Anthropic or OpenAI enterprise agreement, or inside your cloud (Bedrock, Vertex, Azure). Your code is never used to train models.
Agents never hold production credentials
Secrets live in your vault, not on fleet machines. Agents work on code, in branches, behind gates. Deploys stay with your process and your people.
Claude Code or OpenAI Codex, whichever your security team approved
Switch stacks mid-engagement if you need to; the engineer and the workflow stay. We don't resell tokens or licences.
IP assigned per deliverable, as it merges
Code, tests, docs, ADRs and agent configuration are work-for-hire assigned to you as they land, never held against the last invoice. Licence scanning runs before every merge.
Not yet SOC 2 audited, and we say so
As a company launched in 2026 we are not yet SOC 2 audited. Our controls are documented against the checklists your security team already uses and are available in writing under NDA, with compute region options and a data processing agreement covering agent execution.
Proof, honestly
The research we'd cite against ourselves
We have read the same studies you have. The model is built around them, not in spite of them.
Tools alone don't make seniors faster
In a randomized trial, experienced developers were 19% slower with AI while believing they were 20% faster. The speed-up lives in how work is orchestrated, not in the licence.[7]
Gains compound with practice, not the licence
Per-engineer PR throughput roughly doubled, but only after about nine months of accumulated agent use and a redesigned review process. Our engineers arrive at month nine.[3]
Intensity matters
Engineers using command-line coding agents five or more days a week merged about 50% more pull requests; three days a week, about 15%.[8]
Even the labs say review is the bottleneck
Anthropic reports over 80% of code merged into its own codebase is now written by Claude, and warns that raw volume overstates productivity and human review has become the constraint.[9]
Twelve parallelisable tasks, one fleet week
Illustration only: at roughly 2x throughput with review coverage held at 100%, one Fleet Unit covers the output of a small squad. The multiplier you actually get is measured on your engagement and reported every Friday, not printed on this page.
Who we are
Run by engineers who ship. Staffed by engineers you interview.
Apex Fleet is an independent engineering outsourcing firm, founded in 2026. Every engineer on an engagement clears the same bar, is named in your SOW, and talks to you before anything is signed.
- CTO of an AI voice-agent platform in production today: multi-provider agents, a CRM and an integration gateway, run on Kubernetes.
- Runs Claude Code and Codex fleets daily on real product repos. The mechanism on this page is how the founder's own code ships.
- Previously led engineering and infrastructure for data-heavy products on AWS, GCP and Azure.
The bar every engineer clears
New, and saying so once. Apex Fleet launched in September 2026. We won't show you logos we don't have. We'll show you the engineers, the mechanism, the security posture and a Proving Sprint to judge us by.
your-repo/ ├── AGENTS.md or CLAUDE.md · fleet conventions, written by the engineer ├── docs/adr/ · architecture decisions ├── tests/ · agents add, never remove ├── .ci/fleet-gates.yml · every gate, in the open ├── runbooks/ · how to run the fleet without us └── fleet-report.md · every Friday
Engagement and pricing
Priced per Fleet Unit. Compose the team you need.
1 Fleet Unit = 1 staff engineer + their dedicated fleet of coding agents + the machines and model usage they run on. A squad or a delivery team is a number of units, lead included, on one invoice.
1 Fleet Unit / month
- 1 staff engineer, 10+ yrs
- dedicated fleet, 4–8 agents in flight
- dedicated machines
- model usage, fair-use envelope
- review of every change
- weekly fleet report
- hand-off deliverable
- hours
- seats
- tokens
- blended rates
- buyout fees
It isn't headcount
You are not buying a person's hours. You are buying the delivery capacity of a person who works with a fleet, plus their accountability for every merge.
It isn't a tool subscription
Agent compute is a real and rising cost line: in one enterprise rollout, AI spend per developer-month rose roughly 20x.[3] It is inside the unit because a fleet without an operator is the problem we exist to fix.
Start with a Proving Sprint
Two to four weeks on your real backlog, with exit criteria written down before day one: merged PRs, review turnaround, CI pass rate, defects found after merge, against your own baseline. If we miss them, you keep everything merged plus a written hand-off, and walk.
Month-to-month after the sprint
30 days' notice to end, either direction. Need more? Add a unit: another named engineer with their own fleet. Need a lead across units? That is a squad, lead included. Need none next quarter? Stop.
Access
Under your SSO. Machines provisioned. No production access requested.
access completeContext
The engineer reads your codebase and commits the fleet's conventions to your repo. First PRs are deliberately dull.
first PR mergedWorking scale
Fleet at four to eight agents on real tickets. Friday report starts.
fleet at scaleExit review
Against the criteria you helped write. Your team's time: about two hours in week one, then normal PR review.
exit reviewWhen it goes wrong
What happens when it goes wrong
Every failure you're already imagining has a written response.
Questions a CTO asks first
Each answer points to the section that proves it.
Can you staff a whole team, not just one engineer?
Do you only write code, or run the whole cycle?
Will your fleet flood my reviewers?
Who owns the code, and what about licence contamination?
We're standardised on OpenAI, or on Bedrock, or legal only approved one vendor. Do we have to use your favourite stack?
Where do the agents actually run?
How many agents are in a fleet?
When something breaks at 2 a.m., who is accountable?
It's one person. Isn't that a bus factor of one?
How long until the fleet is productive, and what does it cost my team?
How does pricing work?
What if it doesn't work?
Next step
Thirty minutes with the engineer who'd run your fleet.
No salesperson. Bring one backlog item.
- Bring one backlog item. We'll tell you how we'd decompose it, what the agents would do, and what the engineer would refuse to merge.
- You talk to the engineer. The person on the call is the staff engineer who would command your fleet, the same person named in your SOW.
- You leave with a Proving Sprint plan and a written quote. Scope, exit criteria and price, in writing, within two business days.
- Four fields. No commitment. No credit card, no sales sequence.
Sources cited on this page
- DX, State of AI Impact in Engineering, Q2 2026 — 52.7% of code AI-generated across 500+ organisations.vendor research
- Faros AI, "AI Acceleration Whiplash", 2026 — +54% bugs per developer, ~3x incidents per PR, +441% time in review, +31% PRs merged with no review, across 22,000 developers.vendor research
- CMU / Stanford, arXiv 2607.01904, 2026 — 802 developers: review coverage 89%→68%, ~2x throughput after nine months, AI spend per developer-month ~20x.independent study
- Stack Overflow Developer Survey 2025 — 66% cite "almost right" code as top frustration; 3% highly trust AI accuracy.independent survey
- Google DORA, State of AI-assisted Software Development, 2025 — AI as an amplifier; adoption negatively associated with delivery stability.independent research
- Veracode, GenAI Code Security Report, 2026 — security flaw introduced in ~44% of AI code-generation tasks.vendor research
- METR, experienced open-source developer RCT, 2025 — 19% slower with AI; believed 20% faster.independent study
- Microsoft, arXiv 2607.01418, 2026 — +24% merged PRs for CLI-agent adopters; +50% at 5+ days/week; +15% at 3 days/week.observational study
- Anthropic Institute, 2026 — over 80% of merged code written by Claude; volume overstates productivity; review is the bottleneck.vendor research
- Bain Technology Report, 2025 — tool-only adoption 10–15% gains; end-to-end workflow redesign 25–30%.independent research
- US senior engineer hiring benchmarks, 2026 — ~65–75 days to fill. Illustrative for other markets.illustrative benchmark