Staff augmentation services

Staff augmentation services, priced by the pod, not the seat.

Our staff augmentation service is a dedicated pod of senior engineers, mixed to fit the build, working in your repository and your standups from week one. It is not hourly staffing and no one bills you for a seat that is not building. Plans start at $7,500 a month, month-to-month, working within 5 business days.

$7,500
Builder Pod, per month, one build track
$10,000
Growth Pod, per month, two concurrent tracks
5 days
Typical time for a pod to start work
12
Engineer types the bench is mixed from
74
Technologies matched to client stacks
30 days
Cancellation notice, month-to-month, no lock-in

What staff augmentation means when it is a pod

Most engineering staff augmentation places a person against a job description and bills by the hour. You get a resume that roughly matches, a contractor on a clock, and a manager on your side who now owns every architecture call and code review the contractor does not do. We do not sell that. We do not sell hourly staff augmentation, and we do not bill for seats on people who are not building.

A pod is the unit instead: a named lead who owns scope and architecture, a bench of senior engineers mixed to fit the actual work, and QA that runs against the same CI gate as any other pull request. It is priced as a flat monthly number, not a rate card, and it is billed as one flat number rather than a timesheet. Builder is $7,500 a month, Growth is $10,000 a month, and Enterprise is scoped in a meeting for three or more parallel tracks.

That difference, capacity priced by the pod instead of hours or headcount billed by the seat, is the whole reason this page exists separately from a generic staffing pitch. Everything else on this page describes what that actually looks like once engineers are inside your codebase.

Who is on the bench

A pod is not a single title repeated. It is mixed from whichever of these the build actually needs, led by a pod lead who owns the roadmap and reviews every pull request before it merges. Nobody sells these roles separately or bills them at different hourly rates: the bench is sized to the plan, and which types staff a given pod is a scoping decision, not a menu with add-on prices.

  • Forward-deployed AI engineer: sits with your team, learns how the work actually gets done, then automates the parts nobody enjoys
  • AI automation engineer: wires models into the tools you already run so a workflow finishes without a person babysitting it
  • AI / LLM engineer: agents, retrieval and evaluations, plus the harness that proves the answer is correct
  • ML engineer: training, fine-tuning and scoring models, and the pipelines that keep them fed and monitored in production
  • Data engineer: ingestion, warehouses and the joins nobody wants to own, because clean inputs are the difference between a model that works and one that guesses
  • Full-stack engineer: ships the whole slice, schema, API and the screen the user touches
  • Frontend engineer: the interface your customers judge you on, accessible, fast and built to be extended
  • Backend engineer: typed services, background jobs and integrations that hold up under real traffic
  • DevOps / platform engineer: your cloud, your pipelines, your monitoring, so deploys become boring on purpose
  • QA / test engineer: browser and unit coverage on the paths that cost you money when they break
  • Mobile engineer: iOS and Android from one codebase where that fits, native where it does not
  • Pod lead: owns scope, architecture and the weekly delivery, and is your single point of contact

How the pod plugs into your team

The pod works in your repository from day one, not a private branch handed over at a milestone. Every change lands as a pull request against your codebase, a named engineer who owns that piece of the system reviews it, interfaces use typed contracts so a schema mismatch fails at compile time, and tests run in CI before anything merges. Schema changes ship as reviewed, versioned migrations, not a manual change run against a live database.

Standups happen in whatever you already run, Slack, Teams or an email thread, so there is no separate tool to adopt. The pod ships working code every week, not a status deck, and you steer priorities in that standup rather than through a change-order process. Growth and Enterprise plans add a bi-weekly or executive-level strategy call on top of the weekly ship for longer-range planning.

The team runs out of Orange County, California and Prishtina, Kosovo on Central European time, so a US-morning standup is usually reviewing work that was tested overnight rather than work that has not started yet. Code, data and infrastructure are yours from week one with no license-back, so if the engagement ends, whatever shipped keeps running exactly as it did the day before.

What it costs versus hiring or a marketplace

A senior AI or ML engineer hired independently is an estimated $250,000 or more a year fully loaded once salary, benefits and recruiting are counted, and it typically takes 3 to 6 months to close that search. A Builder Pod annualizes to $90,000 a year for a pod lead plus a two-engineer bench, and a Growth Pod to $120,000 a year for a lead plus a three-engineer bench across two concurrent tracks, both starting inside 5 business days.

A marketplace match, the kind a freelancer platform like Toptal provides, books a single contractor fast, often inside 48 hours, at an hourly or negotiated rate with no bench behind that one person. That is a fair tool for a narrow, well-specified role with no ongoing relationship, and we would say so before pitching a pod against it. What a pod adds instead is a named lead who owns architecture for the life of the engagement and a bench that covers if one person is out, at a fixed monthly number instead of a metered clock.

Every figure above besides our own published pod prices is an estimate drawn from public wage data and vendor claims, not a guarantee for your specific hire or contract. Treat any number a staffing vendor quotes you directly the same way: verify it against your own scope before comparing it to a flat monthly price.

How an engagement runs.

  1. 01

    We meet once

    A single session to understand the build track: what exists in your codebase today, what the pod needs to own, and what "done" looks like for the first piece of work.

  2. 02

    We build a free prototype

    A clickable version of the first piece of the work, built before you commit to anything. You keep it either way.

  3. 03

    The pod starts within 5 business days

    The pod lead and senior engineers land in your repository and your cloud account from day one, not a sandbox environment.

  4. 04

    Weekly ships, daily standups

    Progress lands in your existing Slack, Teams or email thread. Working code ships every week, reviewed and tested, not a status report.

  5. 05

    Month-to-month, handover included

    Repository, migrations, deploy pipeline and documentation stay in your accounts throughout. Cancel with 30 days' notice; whatever shipped is already yours.

Shipped, not pitched.

Client names withheld. Engineering described exactly as it shipped.

Political data and campaign-intelligence firm

A campaign operating system built over a unified voter-and-donor graph: ML turnout and persuasion scores per voter, federal contributions matched back to individuals, and choropleth district maps, with new states onboarding through one command.

  • 25.3M voters scored
  • $2.365B FEC contributions matched
  • 3 states, one codebase
Read the build

Developmental-dentistry practice network

A practice-management platform with AI in the clinical loop: dictate a note and a model drafts a structured SOAP entry into the chart, while a vision model reads radiographs and an imaging hub moves CBCT scans through analysis.

  • 80+ REST endpoints
  • 30+ provider pages
  • 2 AI models live (voice + vision)
Read the build

Compounding-pharmacy network

A HIPAA-grade SaaS across clinic, patient and platform-admin surfaces on one design system: pharmacy routing with failover, dual prescriber paths, consent and e-sign, and a seven-year immutable audit log, built spec-first against numbered requirements.

  • 7-year immutable audit log
  • 490+ unit tests
  • WCAG 2.1 AA patient screens
Read the build

Questions buyers ask.

How is this different from hourly staff augmentation?

Hourly staff augmentation places a person against a role and bills by the hour, leaving you to own code review and architecture decisions on top of that bill. A pod is a flat monthly price, $7,500 for Builder or $10,000 for Growth, with a named lead who owns architecture and a code review gate built into the engagement, not something you manage separately. We do not bill for seats on people who are not building.

Can we pick which engineers are on the pod?

The pod is mixed from 12 engineer types, forward-deployed AI engineer, ML, data, full-stack, frontend, backend, DevOps, QA, mobile and more, to fit the actual build, and you can weigh in on composition during scoping. What is not on the menu is billing each type separately or at a different hourly rate; the bench is sized to the plan, not assembled seat by seat.

What time zones does the pod work in?

The team runs out of Orange County, California and Prishtina, Kosovo, which sits on Central European time. A US-morning standup is typically reviewing work that shipped and was tested overnight, rather than waiting on a single time zone to start the day.

How fast can a pod actually start?

Most pods are working within 5 business days of the first conversation, with a free clickable prototype built before that so you know what you are getting before you commit to anything. First shipped work into your repository typically lands in week one or two.

Can we scale the pod up or down?

Yes. Moving from a Builder Pod's one build track to a Growth Pod's two concurrent tracks, or to a custom Enterprise pod with three or more tracks, is a plan change, not a renegotiated contract. Every plan is month-to-month with a 30-day cancellation notice, so scaling down is the same notice period as canceling outright.

Who owns the code the pod writes?

You do, from day one. Everything ships as a pull request into your own repository and your own cloud account or VPC, with full ownership of code, data and IP and no license-back. If the engagement ends, the system keeps running exactly as it did the day before, because nothing in it depends on our infrastructure staying up.

What if an engineer on the pod is not working out?

Tell your pod lead. The pod lead owns staffing within the engagement and can rotate the bench without you having to manage an individual contractor's performance yourself, which is one of the practical differences between a pod and a single freelancer with no one behind them.

Is a HIPAA-regulated build possible with a pod?

Yes. We sign a Business Associate Agreement on request and build to HIPAA-aligned controls, encryption, access logging and audit trails enforced in code under a signed BAA, with a SOC 2 Type II report available under NDA. There is no such thing as HIPAA certification since HIPAA does not issue one, so we do not claim it. We have shipped two production platforms under this posture, including a compounding-pharmacy platform with a seven-year immutable audit log.

Go deeper.

Get in touch.

Thirty minutes to map your problem to a plan and a timeline. You will leave the call with scope, price, and a start date.

What happens on the call
01You describe the outcome you need.
02We map it to scope, price, and a start date.
03You decide whether to proceed to a free prototype.
Schedule a 30-minute call