Outcome Sprint · 1 week · $2,500 · fee credited

Forward deployed AI engineers. On your team. Owning the outcome.

Senior engineers who have shipped AI in production join your standups, repositories and code reviews, and stay until one agreed outcome is live in your product. Start with one dedicated engineer and add more when you need them, always at a fixed quote, never a monthly rate.

  • Within a week

    Our engineer joins your team after you book

  • Not a fit?

    We replace them. Same quote, same outcome

  • Takes longer?

    No extra cost if within the agreed scope

Inside the teams of

In your SlackWorks in your Slack, Jira, GitHub and Cloud
# claims-intake-agent
Northwind Claims
  • Datics engineerMon · StandupJoined today. GitHub and Cloud access is set up, and I am reading the claims intake code.
  • Your tech lead is typing
Starting the Outcome Sprint0 of 5

Illustrative example on a fictional product. Not client work.

Not staff augmentation

Inside your team. Answering for the outcome.

Staff augmentation gives you people and leaves the result to you. A project vendor builds the result somewhere else. Forward deployed gives you both.

Staff augmentation

You rent people.

  • What you buyPeople and hours
  • Who directs the workYou assign the tasks
  • How it is pricedA rate per person, every month
  • How it endsWhen the contract stops being renewed
  • If it takes longerYou pay for the extra hours
  • If the person is not a fitYou manage it, or start again
  • After handoverNothing, once the contract ends
  • What you keepWhatever was written down

The result is still yours to deliver.

Datics forward deployed engineer

Our dedicated engineer, owning your outcome.

  • What you buyA dedicated engineer who owns one outcome in your product
  • Who directs the workOur engineer plans it with your team and owns the delivery
  • How it is pricedA fixed quote for the outcome, not for the engineer's hours
  • How it endsWhen our engineer has the outcome live and handed over
  • If it takes longerOur engineer stays on it at no extra cost, within the agreed scope
  • If the person is not a fitWe replace the engineer. Same quote, same outcome
  • After handoverA two-week warranty: anything short of the done criteria is fixed free
  • What you keepThe code, the tests, and a team our engineer has trained to run it
  • On your team
  • One outcome, owned
  • Your team, stronger

What the engagement looks like

One week to agree the outcome. Sprints until it ships.

Four steps, from a free call to a live outcome your team runs. Every one ends with something you keep.

  1. 30 minutes

    No charge

    Product Review

    You show us the product and the outcome you need. We tell you plainly whether forward deployed fits.

    You keep

    A straight answer on fit

  2. Week 1

    $2,500

    Outcome Sprint

    Our engineer starts within a week of booking, reads the code and agrees the outcome with your tech lead.

    You keep

    Outcome brief and quote

  3. Every two weeks

    Fixed quote

    Build Sprints

    Our engineer works from your backlog, merges through your reviews and releases through your process.

    You keep

    A demo every sprint

  4. When live

    2-week warranty

    Handover

    The outcome is in production, and your engineers have walked through every part of it.

    You keep

    Runbooks, tests and docs

Try it

Pick your outcome. See the engagement.

The steps stay the same for every outcome. What changes is what done means and what each stage delivers.

Pick the outcome you need

Outcome brief · end of week 1

Intake agent drafts claims, and staff approve before filing

Done means

  • Claims drafted from intake documents in the existing screen
  • Each field shows the passage it came from
  • Nothing is filed until a staff member approves it
  • Passes the agreed test set of your own past claims

One fixed quote for this outcome.

  1. Week 1Datics engineerRead the intake code and agreed the approval step with your tech lead.
  2. Sprint 1Datics engineerDrafts and source pages merged. Approval queue next sprint.
  3. HandoverYour tech leadLive for every claims team. Runbook and tests in your repository.

Illustrative example on a fictional product. Not client work.

Sample outcome brief, in action

Week 1

Intake agent drafts claims, and staff approve before filing

Done means0 of 5 passing
  • Claims drafted from intake documents in the existing claims screenAgreed
  • Each field shows the passage it came fromAgreed
  • Nothing is filed until a staff member approves itAgreed
  • Passes the agreed test set of your own past claimsAgreed
  • Runs in your Cloud account under your users' permissionsAgreed
Depends on
Write access to the claims API
Price
One fixed quote

Your claims screen · Claim CL-2291

Before

Adjuster retypes the claim from intake.pdf, 12 pages

Claimant
Policy
Incident
Date of loss
Saved as a draftApprove

Illustrative example on a fictional product. Not client work.

Outcome not clear yet?

Start with the Planning Sprint.

If the outcome is unclear or too large for a week, we say so in the Product Review. The two-week, $5,000 Planning Sprint maps it first, and its fee counts toward the build too.

See the Planning Sprint

No lock-in

Stop after Week 1 and keep the brief.

The outcome brief, with what ships, what done means and how it is tested, is yours whether or not you continue with us.

Know the outcome you need?

In 30 minutes we tell you whether forward deployed fits, and what Week 1 would define.

Book a 30-minute Product Review

In practice

How it ran inside our clients' teams.

Six products, six teams, and how our engineers worked inside each one.

Real estate and hospitality

CleanHaus

Took its AI operations agent and a new React Native app live, inside its own product.

How it ran

  • Access granted by CleanHaus's CTO to its own GitHub, AWS and Cognito
  • Shipped through its pull requests, reviews and Slack, with its CTO setting priorities
  • Recordings and live walkthroughs of each feature before users saw it
App and AI agent liveCase study

Automotive and dealerships

Coast Technology

Grew a live dealer portal into a CRM and engagement platform, without a core rewrite.

How it ran

  • Our engineers work one backlog with Coast's product lead every sprint
  • Built and run inside Coast's own AWS and Google Cloud accounts
  • Every release goes to a demo environment before production
Shipping every sprintCase study

Sales training (EdTech)

Insurance Sales Lab

Built call tracking, team dashboards and team admin inside its own platform, which led ISL to hire us for two AI products.

How it ran

  • Every feature built in ISL's own repository and stack
  • Priorities set by ISL in daily syncs
  • One point of coordination, so ISL had one place to raise priorities
Hired again twiceCase study

Healthcare practices

Peerlogic

Turned raw phone events into trusted call records for its practice AI, inside its own product.

How it ran

  • Scope set with Peerlogic's CTO before any build
  • Every change through its pull requests and CTO review
  • Built in Peerlogic's own Google Cloud environment
RenewedCase study

Healthcare

Datascape

Reads compensation terms from any physician contract, inside its own HIPAA cloud.

How it ran

  • Onboarded into its Slack, GitHub and AWS under a BAA
  • A versioned release every week for its team to test
  • Code, docs and a walkthrough left in its own account
Live, hired againCase study

B2B software

BlueID

Built a new access feature into its live digital key platform and shipped it to production.

How it ran

  • Worked in BlueID's issue tracker, wiki and chat
  • Weekly goals and retros with its architect
  • Documented, then handed to BlueID's backend team
Live in productionCase study

What clients say

What it is like with our engineers on the team.

The founders and CTOs whose teams we joined, in their own words.

CleanHaus · App and AI agent live

“CleanHaus has been moving quickly to deploy our app and Broomy AI Agent with the key assistance of the Datics team. We couldn't have reached this point without their excellent bench of engineers.”
Nat ParkerCEO and Co-Founder, CleanHausCase study

Datascape · Live, hired again

“Umair is a proven professional who knows what it takes to get things done. His engineers have a deep well of knowledge they can tap for tackling complex development problems. I'm looking forward to continuing work together.”
Jordan EmrieCTO, DatascapeCase study

Coast Technology · Shipping every sprint

“You've always achieved everything that we've asked for, and it's amazing. The quality of your work is second to none, and we couldn't be more pleased.”
Rich DeLanceyCo-Founder and CIO, Coast TechnologyCase study

Summers & Company · Tested and delivered

“What stood out to me was consistency: the work was built, tested, and delivered without noise.”
Dr. Timothy C. SummersCEO, Summers & CompanyCase study

CleanHaus · Every feature walked through before release

“I want to recognize and let you know that your work is having a truly positive outcome. Our recent tests are going so much better!”
Matthew RotterCTO, CleanHausCase study

5.0 average client rating

Which engagement fits

Built with your team, or built for it.

Three ways to work with Datics. Forward deployed is the one where we build alongside your engineers.

Planning Sprint

You know you need AI but not yet what to build.

We study your product and hand you a ranked plan and a fixed quote. $5,000, two weeks.

Learn more about the Planning Sprint

Product build

You want a capability delivered and your team is busy elsewhere.

Our team builds it in your code and cloud at a fixed quote, and hands it over.

Learn more about the Product build

Forward deployed

You know the outcome and want it built with your team, not for it.

Our engineer works inside your team until the outcome ships, at a fixed quote. Starts with a one-week, $2,500 Outcome Sprint.

Book a 30-minute Product Review

Try it

Not sure which one fits?

Four questions, and we show the start that fits your product, with what it costs.

  1. 01Is your product live, with customers using it?
  2. 02Have you already built an AI feature or agent?
  3. 03Do you know the outcome you need?
  4. 04Do you have engineers who would work alongside ours?

Four questions

Find the right way to start.

Answer all four and we show the start that fits your product, with what it costs. Your answers go with your booking, so the call starts where you are.

Questions

Forward deployed engineering, answered.

What is a forward deployed engineer?

A forward deployed engineer (FDE) works inside a customer's own product, code and team to make a specific outcome real in production. The role was made well known by Palantir. At Datics it means our engineers join your repositories and rituals to ship one outcome you agreed with us, then hand it over.

Who is forward deployed engineering for?

Software companies with a live product and their own engineering team, who know the outcome they need and want it built inside that team rather than handed over from outside. If the outcome is not clear yet, the Planning Sprint is the better start.

How is this different from staff augmentation or hiring contractors?

With staff augmentation you rent people and direct their hours. A forward deployed engagement is priced and planned around one outcome: we agree what ships and what done means, own the delivery with your team, and finish when it is live and handed over, not when a contract runs out.

Why not just hire our own AI engineer?

For work that never ends, you should. For one outcome you need now, a hire takes time to find and still has to learn production AI on your product. Our engineers start within a week, have shipped AI in production before, and leave your team able to run what they built.

What does a forward deployed engagement cost?

It starts with the Outcome Sprint: one week, $2,500, with our engineer working inside your team to define the outcome. You then get a fixed quote for that outcome, and the sprint fee counts toward it. There is no monthly rate per engineer.

Who are the engineers?

Senior Datics engineers who have shipped AI in production inside live products, in stacks such as AWS and Azure, React and React Native, and agent frameworks such as LangGraph. Most engagements start with one dedicated engineer. If the outcome needs more, or you want to move faster, we add engineers, always inside a fixed quote. They are backed by the wider Datics team on architecture and applied AI.

How soon can an engineer start?

Within a week of booking the Outcome Sprint.

Can we meet the engineer before we start?

Yes. You meet the engineer who will join your team before the Outcome Sprint starts, and you can ask them anything about how they would approach your outcome.

What if an engineer is not the right fit for our team?

We replace them. The outcome and the fixed quote stay the same, and the work already done stays in your repositories.

What if the work takes longer than planned?

Within the agreed scope, that is on us: the fixed quote does not change. If you add to the scope, we agree the change and its price with you before any work on it starts.

Can we stop after the Outcome Sprint?

Yes. The outcome brief, with what ships, what done means and how it is tested, is yours to keep whether or not you continue with us.

Who owns the code and the work?

You do. The work lives in your repositories and cloud accounts from the first day, and everything we build is yours when the outcome is handed over.

How do you keep our code and data secure?

Our engineers work only inside your accounts, with the access you grant and can revoke at any time. Every change goes through your own code review, the work stays in your repositories and cloud from day one, and we work under your NDA, or a business associate agreement where health data is involved, as we do for Datascape.

What happens after handover?

Every outcome comes with a two-week warranty after handover: anything that does not meet the agreed done criteria is fixed at no extra cost. Further work after that is quoted as a new outcome, only if you want it.

Who do we talk to if something is not right?

Our engineer first, every day. Above every engagement is Umair Majeed, our founder and CEO, based in Austin, Texas, and you can reach him directly.

How do your engineers work with our team?

Inside your tools: your repositories, tickets, reviews and planning. They demo every two-week sprint to your team and make product and architecture calls together with your people, so your team knows the work well enough to run it after handover.

What kinds of outcomes fit this model?

Outcomes inside a live product that need engineers close to the code and the team: an AI feature or agent, a data foundation the AI depends on, a module rebuilt without stopping the product, or an integration with systems you already run.

Have an outcome your team cannot get to?

Show us the product and the outcome. In 30 minutes you will know whether a forward deployed engagement fits, and what the Outcome Sprint would define.