Healthcare · Clinical AI
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Forward deployed engineers
The code was never the bottleneck.
The waiting was. So we took it out.
One senior engineer takes the whole thing. They scope it with your team, build it, ship it, and answer for it once it’s live. No spec thrown over a wall. No queue to sit in.
Free consultation · No commitment · Response within 24 hours
AR
Your forward deployed engineer
Scopes · Builds · Ships · Owns
One feature. Two ways to deliver it.
Working day 70
The old way
6 roles · 5 handoffs
Shipped
70working days
The new way
1 FDE · 0 handoffs
Shipped
10working days
Someone actually working
Waiting on someone else
One owner, no gates
24
Hours to a shortlisted engineer, not weeks of recruiting
18+
Products shipped across health, fintech, retail and education
16
Core stacks on the bench, from .NET to React Native to LLM tooling
2
Time zones covered: Mountain View, CA and Islamabad, PK
The bench, in practice
The model
A forward deployed engineer is not a resource you rent. It’s a person who owns the outcome.
The term comes from deployed-engineering teams at data companies, where the engineer sat with the customer instead of behind an account manager. We run the same shape: one senior engineer, embedded in your context, accountable end to end.
How it usually goes
You hire capacity
- You write the spec, because the developer doesn’t know the business.
- Requirements pass through a PM, then a BA, then a designer, then a dev.
- Every clarification is a ticket and a two-day round trip.
- When it breaks in production, nobody on the chain is the owner.
Forward deployed
You hire an owner
- They sit in your standups, read your support tickets, learn your domain.
- The spec is a conversation, not a document handed across a wall.
- They choose the stack, build it, deploy it and hold the pager.
- One name to ask, one name accountable, from day one to production.
The math
Six specialists have fifteen conversations. One engineer has none.
Every person you add to a delivery chain adds a link to every other person. Six roles means fifteen two-way channels for a requirement to blur, and five places for it to wait. Hover a role to see what a forward deployed engineer absorbs.
The traditional delivery chain
6 roles · 15 communication paths
Hover any role to see what that person really contributes to the delivery, and who ends up carrying the very same work when a single engineer is deployed instead.
15
Comm. paths
5
Handoffs / feature
6
People to brief
One forward deployed engineer
1 person · 1 direct line to you
Same six jobs, one owner. Scoping, design decisions, architecture, implementation, deployment and support sit with the person who understood the problem in the first place.
0
Comm. paths
0
Handoffs / feature
1
Person to brief
The fair question
If AI writes the code, what exactly are you paying an engineer for?
Honest answer: not the typing. Our engineers use the same assistants you’d use. The difference is everything that happens around the generated code, which is where projects actually fail.
Prompt-only build
Ships fast, then stalls
- Working demo in a weekend, unreviewed data model underneath it.
- No tests, so the third feature quietly breaks the first.
- Nobody notices the auth gap or the unbounded query until a customer does.
- Month four, velocity is zero and the rewrite conversation starts.
Engineer with the same tools
Ships fast and keeps shipping
- Every generated diff is read, questioned and often rewritten before merge.
- Tests, error budgets and evals for anything model-driven.
- Monitoring and rollback set up before launch, not after the incident.
- A codebase your next hire can read, because someone was accountable for it.
What the data says
Independent research · 2025–2026
44%
of AI code-generation tasks introduced a risky security vulnerability. Across a year of dramatic model progress the security pass rate moved from 55% to 56%. Syntax improved. Security did not.
Veracode · July 202619%
slower. In a randomised trial, experienced developers took longer on real tasks in their own repositories when using AI, while estimating it had made them 20% faster.
METR · 2025 randomised trial95%
of enterprise GenAI pilots delivered no measurable impact on P&L. The blocker wasn’t model quality. Nobody closed the gap to the actual workflow.
MIT NANDA · 2025 · 300 deployments
And the finding that decides it: in the MIT study, AI initiatives built entirely in-house succeeded roughly a third of the time. The ones built with a specialist partner succeeded about twice as often. The tool was never the variable. Who owned the work was.
Same toolbox, both columns
Claude CodeCopilotCursorGPT-based agents
The tools are identical. What you’re buying is judgement about what to keep, and someone whose name is on it in six months.
“AI doesn’t fix a team; it amplifies what’s already there.”
Google DORA, 2025 · 90% of developers now use AI daily
Selected work
Products our engineers scoped, built and still support.
Education · Assessment
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What clients say
The pattern in the feedback is always the same word: self-starting.
“Working with the experts from Zeki was a game-changer. Their skills and communication were top-notch.
“Each developer I had worked with from Zeki Experts was talented, efficient, communicative, and self-starting.
“Working with the team at Zeki Expert Solutions has been a pleasure. They are professional and efficient.
“Zeki Experts’ team was exceptional: talented, efficient, communicative, and self-starting.
Getting started
Three steps, and the clock starts the day you call.
A real sequence, not a diagram. Each step depends on the one before it.
STEP 01
Tell us the problem
Thirty minutes on a call. Not a requirements gathering session. We want the actual business problem, the constraint you’re working against, and what “done” looks like to you.
Day 0 · 30 minutes
STEP 02
Meet the shortlist
We put forward engineers from the vetted bench whose domain and stack match what you described. You interview them yourself. No profile padding, no bait and switch.
Within 24 hours
STEP 03
Deploy into your team
Your engineer joins your tools, your standups and your context, and starts shipping. If the fit isn’t right, we replace them, and you don’t pay for the ramp-up twice.
Shipping inside 2 weeks
Questions
The things people ask before the first call.
Staff augmentation gives you hands to execute a plan you’ve already made. A forward deployed engineer helps make the plan. They’re expected to push back on the brief, propose a simpler path, and own the result. That only works if they understand your business, not just your ticket queue. We do straight augmentation too, and we’ll tell you honestly which one your situation calls for.
Roughly: sit in your standup, talk to whoever owns the problem, write code, review what the AI wrote, deploy it, and watch it in production. The unglamorous half is the point. They’re reading your support tickets and asking your operations lead why a workflow exists, because that’s where the requirements actually live.
For a lot of work, yes, and it’s faster precisely because there’s nobody to hand off to. For larger programmes it isn’t, and we’ll say so. The usual shape is one forward deployed engineer who owns the outcome, with specialists pulled in from the bench for defined pieces (a mobile build, a data migration, a security review) rather than a standing six-person team billing from week one.
A flat monthly rate per engineer, billed for the time they’re deployed, with a notice period rather than a lock-in. No separate line items for project management, coordination or handover, because there aren’t any. We’ll quote against your specific scope on the first call.
No. Your engineer joins your Jira, your Slack, your repo, your release process. The one thing we ask for is direct access to whoever owns the problem. If every question has to travel through a coordinator, you’ve rebuilt the chain this model exists to remove.
Tell us early and we replace them from the bench, and we don’t bill you for the second ramp-up. Fit is our risk to carry. We picked the shortlist.
Engineering is in Islamabad, Pakistan, with a US presence in Mountain View, California. In practice that means a working overlap with US mornings and European afternoons, and a written handover culture for everything outside it.
Next step
Bring us the problem, not the spec.
Thirty minutes, no commitment, and you’ll leave the call with a straight answer about whether one deployed engineer is the right shape for what you’re trying to do, including when it isn’t.