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AI Agent Development Company in London

By Sahil Kataria, Chief Executive Officer, QServices

Sahil Kataria is the CEO of QServices, a Microsoft Solutions Partner delivering AI agents and custom software for regulated industries. He leads enterprise AI strategy and FinTech delivery. LinkedIn ↗

Written from QServices' hands-on delivery work and reviewed by Rohit Dabra, Chief Technology Officer, QServices, before publishing.

QServices is a remote-first software consultancy serving London businesses in FinTech, Insurance, Legal, and Media. We are not headquartered in London, but we work with UK clients on AI agent development engagements with four hours of daily GMT morning overlap between our India team and your London office.

What London buyers typically need from AI agent development

London's financial services sector operates under some of the tightest compliance requirements in the world. Firms regulated by the FCA or PRA cannot deploy AI agents that make decisions without audit trails or override controls. Every agent we build includes a human-in-the-loop (HITL) design phase, where we map which decisions require human review before reaching a customer or a regulated system.

Common project types from London buyers:

All projects for UK clients are scoped with UK GDPR compliance by default. FCA-regulated clients typically need additional compliance documentation, adding 15 to 25 percent to project cost. PRA-regulated firms may require separate sign-off on the HITL governance layer. The Financial Conduct Authority expects firms deploying AI in regulated workflows to maintain clear accountability and human oversight at every decision point.

How we work with London clients

Our engineering team is in India (IST, GMT+5:30). London runs on GMT. That gives us four hours of real-time overlap each weekday: 9am to 1pm GMT, which is 2:30pm to 6:30pm for our team. All sprint calls, demos, and architecture reviews happen inside that window.

Each two-week sprint follows this cadence: a Monday kickoff call with your product owner or delivery lead, daily async status updates posted to a shared Teams or Slack channel by 10am GMT, a mid-sprint check-in on Wednesday, and a Friday demo. Code reviews run through Azure DevOps or GitHub with a 24-hour turnaround on pull request comments.

We do not maintain a London office. For engagements above $60,000, we are open to a milestone review visit, with travel costs passed through at cost. Most clients prefer the speed of async delivery and find the four-hour overlap window sufficient for all live coordination.

Relevant work in similar markets

We do not have a published case study for a London FinTech or Insurance firm. Our closest published work covers adjacent regulated financial and operational workflows.

For Melegacy, an investment management and legacy planning platform, we built an AI agent using Microsoft Copilot Studio that connects to the Nasdaq API for ML-powered stock predictions and investment recommendations based on user portfolio amounts. The same agent manages legacy sharing with nominees and charity disbursements in a single chatbot interface. This is the kind of regulated financial workflow that London wealth management and insurance operations ask us to build.

Case Study

AI Investment and Legacy Management Chatbot (Melegacy)

Investment management and legacy planning platform

ML-powered stock predictions from Nasdaq historical data with investment recommendations based on user amount

Legacy sharing with nominees and charity management in a single Copilot Studio chatbot

Microsoft Copilot StudioNasdaq APIMachine Learning

For an IT services company, we built Smart PM, an AI project management agent on Azure AI Foundry that captures meeting transcripts via Fireflies.ai, creates Azure DevOps backlog items with Fibonacci story point estimates, and generates real-time Power BI sprint velocity dashboards, replacing manual meeting note capture entirely.

Case Study

AI Project Management Bot for Azure DevOps and MS Teams (Smart PM)

IT services company

Automated meeting transcript capture and backlog creation in Azure DevOps with Fibonacci story point assignment and sprint capacity tracking

Real-time Power BI sprint velocity dashboards replacing manual meeting note capture and task allocation

Azure AI FoundryAzure AI SearchPower AutomatePower BIMS Teams

Neither project was based in London, but both required AI agents operating on structured data inside governed, auditable workflows. That pattern is what London FinTech and Insurance buyers consistently describe when they contact us.

What AI agent development costs for a typical London project

Our projects are priced in USD. For London clients, typical engagements run from $15,000 to $85,000 over 6 to 12 weeks. Currency conversion at the time of scoping is at your discretion.

FCA or PRA regulated scope adds 15 to 25 percent for compliance documentation and HITL audit trails. Each non-trivial integration, such as a legacy insurance platform, a legal case management system, or a trading data feed, adds $3,000 to $12,000. See our AI agent development cost breakdown for a full walkthrough.

How to start working with us

Three steps to get started:

  1. Discovery call (30 minutes): You describe the workflow you want to automate. We ask about your systems, compliance scope, and where human oversight is required.
  2. Scoping document: Sent within three business days, covering recommended architecture, HITL design, timeline, and a fixed-price estimate.
  3. Project start: Sprint zero covers environment setup, access provisioning, and data mapping.

Use the contact form on this page to book a discovery call, or visit our contact page.

Can you work with London companies remotely?

Yes. All our London engagements run fully remote. Four hours of GMT morning overlap covers sprint ceremonies, demos, and live architecture reviews. We use Microsoft Teams or Slack for day-to-day communication and Azure DevOps or GitHub for code and project tracking.

For UK clients, we scope Azure deployments to UK South or UK West regions by default to satisfy UK GDPR data residency requirements. FCA and PRA compliance obligations are addressed in the architecture specification before build starts. We include a privacy impact assessment template in our standard project agreement, and data does not transit through non-UK-approved regions without explicit written approval from your team.

Ready to discuss your project?

Share your requirements with QServices. Our engineers will give you a straight answer on fit, timeline, and cost — no sales scripts.

Book a Free Consultation
Frequently Asked Questions
Do you have an office in London? +
No. QServices is based in India and works with London clients on fully remote engagements. Our team operates on IST (GMT+5:30), giving us four hours of real-time overlap with London each morning, from 9am to 1pm GMT. Sprint calls, demos, and architecture reviews all happen within that window.
What is the time difference between London and your India team? +
London operates on GMT; our team is on IST (GMT+5:30), a five-and-a-half-hour difference. Our afternoons align with your mornings. We schedule all live meetings between 9am and 1pm GMT, which is 2:30pm to 6:30pm for us, and manage everything else asynchronously through Teams or Slack.
Have you worked with companies in the UK before? +
We do not have a published UK case study yet. Our closest published work is for Melegacy, an investment management and legacy planning platform, where we built a Copilot Studio agent with Nasdaq API integration for regulated financial workflows. We are transparent about where we stand and do not claim local experience we have not yet built.
How do you handle UK GDPR and FCA compliance requirements? +
For UK GDPR, we default to Azure UK South or UK West regions and include a privacy impact assessment in our project agreements. For FCA-regulated engagements, HITL audit trails are built into the agent architecture from day one, with 15 to 25 percent additional budget for compliance documentation. PRA-regulated projects receive separate governance sign-off on the oversight layer.
What AI agent use cases are most common for London FinTech and Insurance firms? +
The most frequent requests are KYC and AML screening agents, insurance claims triage automation, and regulatory reporting assistants. All require human-in-the-loop controls at key decision points. That HITL design phase is a standard part of every engagement we run, not an add-on, which is why firms in FCA and PRA regulated workflows come to us.
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Sahil Kataria

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Phil J.
Phil J.Head of Engineering & Technology​
QServices Inc. undertakes every project with a high degree of professionalism. Their communication style is unmatched and they are always available to resolve issues or just discuss the project.​

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