SFT · expert generation
Demonstrations
Worked examples from people who do the job: clinical reasoning, contract analysis, financial modelling, production code.
Frontier AI · FDE as a service
AI engineers who build inside your team.
Kitsune provides forward-deployed engineering for AI as a service. Our engineers join your team, work in your codebase and turn the workflow you need into a system your business can run.
✓ Embedded in your team✓ Building in your stack✓ Accountable for delivery
Forward-deployed AI engineering
Forward-deployed engineering
An engineer building in your stack.
Your FDE works with the people who own the problem and writes production code in your stack. They build the agents, connect the tools and test the workflow with your team, then document it so your engineers can run it.
- 01
They sit where the problem is
In your standups, your repo and your incident channel. The distance between the person who understands the workflow and the person writing the code goes to zero.
- 02
They write production code
Agents, tools, retrieval, evaluation harnesses and the plumbing between them. Reviewed by your engineers, merged into your repositories, owned by you.
- 03
They build the eval before the demo
A capability nobody can measure is a capability nobody will sign off. The harness that proves the thing works gets built alongside the thing itself.
- 04
They hand it over and document it
The engagement ends with your team running the system without us. Anything else is a dependency we sold you, and it would show up in the second invoice instead of the first.
Where the work sits
Put AI to work inside your business.
Bring us the workflow that needs building or the AI project that has stalled. We put an engineer alongside your team to work through the systems, data and decisions it depends on.
Integration
Connect your existing systems
Wire AI into the tools and data your team already uses, so the work can move through the whole process.
Forward-deployed engineering
Build with your team
An engineer in your repository and working meetings, responsible for getting the workflow into production.
Agent development
Build the agents that do the work
Agents, retrieval and evaluation tools built around the task your business needs done.
Start with one workflow
Tell us what you need built.
Scope
Define the first build
Show us the workflow, your tools and what a working result looks like. We agree the scope and the engineer you need.
Embed
Put an engineer in your team
Your FDE joins the people doing the work, gets into your codebase and starts building against your actual systems.
Ship
Run it against real work
Your team tests the workflow with us. We put it into production with the code, tests and documentation your engineers need.
Model training and evaluation
Specialist support when the model needs it.
For teams that also need training data or model evaluation, we supply domain specialists for demonstrations, ranking, testing and red-teaming.
Preference · RLHF
Ranking and preference
Pairwise judgments against your rubric. Inter-rater agreement gets measured and reported with every batch.
Evals
Evaluation and grading
Rubric design, benchmark grading and regression suites, built by people who run eval harnesses on their own systems.
Safety
Red-teaming
Adversarial probing and jailbreak discovery, written up so your safety team can reproduce and act on every finding.
Multilingual
Urdu and regional languages
Native fluency in Urdu, Punjabi, Sindhi and Pashto alongside professional English — coverage most vendors quietly outsource.
Agents
Agent evaluation
Task-based testing in real environments — browsers, codebases, workflows — scored against criteria you define up front.
How you get it
One team that stays on your account.
You brief a pod once. It keeps the context, the corrections and the standard, and it is still there next quarter.
- 01
We source for your domain
Graduates and practising professionals out of LUMS, NUST, IBA, FAST and GIKI, plus licensed specialists where the work needs a credential.
- 02
They get screened before they touch your systems
Language assessment, domain testing and a reasoning screen. We publish the pass rates so you can see what the filter actually removes.
- 03
The pod calibrates to your rubric
They train against your guidelines until agreement clears the threshold you set, and we absorb the cost of getting them there.
- 04
Work ships with its own evidence
Every batch arrives with sampling results, double-marked disagreements and the agreement rate attached.
- 05
The same people stay on your account
Context compounds instead of resetting. Your rubric does not get re-explained to a new stranger every week.
Where the supply comes from
Pakistan is the talent pool nobody is looking at.
The same labs paying US rates for expert hours are competing for people who work remotely anyway. Pakistan already exports this work through freelance platforms at scale. We package it with vetting, calibration and accountability.
$4.5BPakistan IT exports, FY2026, up 29% year on year
$950MFreelance earnings in ten months
Top 5Country on global freelance platforms
5Universities feeding the vetting funnel
Built to pass your vendor review.
Procurement asks the same questions every time. Here are the answers before you ask: every contributor signs an NDA before their first task, access is least-privilege and revoked on rotation, and work runs inside your stack when your policy requires it.
SOC 2 Type II and ISO 27001 are still on the roadmap. Until they land we start you on non-sensitive and public-data pilots, and we say so up front rather than letting you find out in diligence.
NDA before first task
Signed by every contributor. Client work is never reused, resold or shown in a portfolio.
Least-privilege access
Scoped credentials, revoked on rotation, with an audit trail per batch.
Measured QA
Sampling, double-marking and agreement rates reported with the work.
Pilot first
A bounded batch before any commitment. Judge the output, then scale the pod.
Your tools
We work inside your annotation stack, so nothing migrates and no data leaves your perimeter.
Named supervision
A pod lead who answers for quality, reachable in your timezone overlap.
How this is bought today
Three ways to buy expert work, and what each one costs you.
Most teams have already tried at least one of these. The differences show up in rework, not in the first invoice.
| Crowd marketplace | Traditional BPO | Kitsune pod | |
|---|---|---|---|
| Who does the task | Whoever claims it that hour | Whoever is on shift | A named pod that stays on your account |
| Domain credential | Self-declared | General graduate pool | Tested, and licensed where the work needs it |
| Calibration to your rubric | You write guidelines and hope | Billed to you as training hours | Done before billing starts, at our cost |
| Quality evidence | Spot checks you run yourself | A throughput report | Agreement rate and double-marked disagreements per batch |
| Context between batches | Resets every time | Resets on rotation | Same people, corrections compound |
| Who answers when quality slips | Platform support | An account manager | The pod lead who signed the batch |
| Language coverage | English-first | English-first | Professional English plus Urdu, Punjabi, Sindhi, Pashto |
Common questions
Working with a Kitsune engineer.
What does forward-deployed AI engineering as a service mean?
We put an AI engineer inside your team to build and deploy the systems you need. They work with your people, in your codebase and against your workflow. Kitsune supplies the engineering capacity and takes responsibility for delivery.
How do you choose the engineer for our team?
We start with your workflow and technical stack, then match the engineering skills to the build. Our engineers work on the AI systems Kitsune runs, including agents, integrations, retrieval and evaluation.
How do you know the system works?
We agree what the workflow needs to do and build the tests alongside it. Your team reviews the code and tests the system against real tasks before it goes into production.
Do you have SOC 2 or ISO 27001?
Not yet. Both are on the roadmap and neither has landed. Until they do we start clients on non-sensitive or public-data work, and we say so here rather than letting it surface halfway through your vendor review.
Can the work run inside our own tooling?
Yes. Our engineers work in your repositories, connect to your existing tools and build around the way your team operates.
Who owns the code?
You do. The code goes into your repositories, with the tests and documentation your team needs to run it.
Why Pakistan?
The country already exports this class of work at scale through freelance platforms, at rates well under US and European equivalents, with a large English-fluent graduate pipeline out of LUMS, NUST, IBA, FAST and GIKI. What has been missing is a vendor wrapping that supply in vetting, calibration and accountability. That is the whole business.
What timezone overlap do we get?
Pakistan Standard Time is UTC+5, which gives you a full working overlap with Europe, the Gulf and India, and a morning overlap with the US east coast. Pod leads are reachable inside your working hours, not at the end of a queue.
Can you also help with model training and evaluation?
Yes. We supply domain specialists for demonstrations, preference ranking, evaluations and red-teaming. That work can support an engineering engagement or run as its own project.
Forward-deployed AI engineering
What do you need built?
Tell us the workflow, the tools you use and where the work gets stuck. We will scope the build and the engineer your team needs.