AI agent development in London
We build AI agents that take real actions in the systems of UK businesses, working remotely from our team in Pakistan. Permissions, human review and data protection are settled before the autonomy, because in a regulated UK firm that is the part that decides whether it can go live.
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London
AI Agent Development for London
An agent is worth building when it acts rather than answers: it works a queue, updates the CRM, reconciles the exceptions, drafts the response a person then sends. In London that appetite is strongest exactly where the governance burden is heaviest, in financial services, insurance, legal and healthcare, which means the interesting engineering is not the model. It is the boundary around it.
UK GDPR is the constraint that shapes the design most. Where a decision produces a legal or similarly significant effect on a person, there are real limits on doing it by automated means alone, and meaningful human involvement is not a checkbox on a screen. It has to be a person with the authority and the information to actually change the outcome. Personal data used by an agent also needs a lawful basis, a retention position and a defensible answer on what is sent to a third-party model. These are answerable questions, but they need answering before the build rather than during a DPIA two weeks before launch.
For firms trading into the EU there is now the EU AI Act to think about as well, and for FCA-regulated firms there are the existing expectations on outsourcing, operational resilience and being able to explain a decision to a customer or a regulator. Those expectations reach the supplier too. Our team works from Pakistan and Yarqat has no UK office, so we expect your third-party risk process to ask where we are, who can reach what, and how the agent keeps running if we stop working together, and we would rather answer all three in the first week than the last.
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What is specific
Built for London
Meaningful human review where it is required
Where an agent decision affects a person in a legal or similarly significant way, UK GDPR limits doing it by automated means alone. We design the human step to be real: a person with the information and the authority to change the outcome, not a rubber stamp on a screen. That is both the lawful position and the one your DPO will sign off, and it is far easier to build in than to add.
Permissions in the system, not the prompt
The agent holds only the permissions it needs. Anything irreversible, anything that moves money and anything that reaches a customer in your name sits behind an approval by default. Prompts can be talked around, permissions cannot, so the boundary belongs in the architecture. Scope widens once the agent has earned it against measured results rather than on the strength of a good demo.
Explainable after the fact
Every action is logged with what the agent saw, what it decided and what it changed, in a form a non-engineer can read. For an FCA-regulated firm that is what makes a decision explainable to a customer or a regulator months later, and for everyone else it is what makes the system recoverable the first time it gets something wrong, which it eventually will.
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Scope
What we build
Project delivery, owned end to end, for London clients.
- Operations agents that work a queue, reconcile exceptions and update systems of record, with escalation rules agreed up front
- Document agents for contracts, claims and onboarding packs, extracting what matters and flagging what they are unsure of
- Customer-facing drafting agents where a person reviews and sends, keeping the human in the loop by design
- Permission models, approval queues and hard limits around irreversible or externally visible actions
- UK GDPR groundwork: lawful basis, data minimisation, retention and a defensible position on what reaches a third-party model
- Human-readable action logs plus an evaluation harness measuring accuracy, escalation rate and cost per task
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Also in this city
What else we build in London
AI Agent Development in London: common questions
How does a supplier in Pakistan fit our outsourcing and risk process?
Openly. Yarqat is registered in Islamabad and our engineers work from Pakistan, so your risk and compliance teams will reasonably want to know where access sits, how the agent is operated day to day, and what happens if the relationship ends. We document all three: our access is scoped and logged in your environment, the runbook is written for your people, and the code and infrastructure belong to you from the start. Whether that meets your own obligations is for your compliance function to decide.
Does UK GDPR allow an agent to make decisions about people?
It depends on the decision. Where the effect on a person is legal or similarly significant, there are real limits on relying on automated processing alone, and meaningful human involvement is required rather than a nominal review step. We design that human step to be genuine, with the information and the authority to change the outcome, and we settle the lawful basis and retention position before building rather than during a rushed DPIA.
What about the EU AI Act?
If you place a product on the EU market or your system affects people in the EU, it is in scope wherever it was built. The practical implications are mostly things worth doing anyway: knowing what your system does, documenting it, keeping a human in the loop for consequential decisions, and being able to explain outputs. We build to that standard by default and will tell you where your use case needs specialist legal advice rather than pretending we are it.
How do you stop an agent doing something damaging?
The permission model, not the prompt. The agent holds only the access it needs, irreversible actions require a person, and anything that reaches a customer in your name goes through approval by default. We also make it fail safely: when the agent is unsure it escalates rather than guessing, because a confident wrong action is far more expensive to unwind than a delayed one.
How do we prove the value before expanding it?
By measuring a narrow scope first: accuracy on real cases, escalation rate, error rate when it does not escalate, and cost per task. Those numbers are what should justify widening the agent, not a demonstration. It is also what makes the business case defensible internally, which in a regulated firm is usually the harder part. The review of those numbers happens in the window where your morning overlaps our afternoon.
AI agent development in London?
Tell us what you are building. We serve London remotely, with no local office and no account manager in between, so the person who reads this is the one who would run the work.
- 01A senior engineer reads it. Not a form queue, and not an account manager.
- 02We reply either with questions or with a straight answer that we are not the right fit.
- 03If it looks like a fit, a technical call with the person who would actually run the delivery.
- 04Then scope, effort and risk in writing, before anyone signs anything.