Generic AI tools give generic results. Your business needs an AI agent built for your specific problem.
We build custom AI agents trained on your data, integrated into your systems, and deployed in your environment — not a chatbot wrapper around ChatGPT. An agent that does real work in your real context.
What kind of AI agent does your business need?
Every custom agent starts with a specific problem to solve. These are the most common agent types we build — each one scoped, priced, and delivered as a finished product.
Knowledge & Q&A agent
Answers questions from your internal documentation, product data, or knowledge base. Always accurate, always sourced.
Customer support agent
Handles inbound queries, resolves common issues, escalates to humans when needed. Works across chat, email, or Teams.
Sales & lead qualification agent
Qualifies inbound leads, gathers requirements, books meetings, and populates your CRM — without human involvement.
Data processing agent
Monitors data sources, extracts insights, generates summaries, and triggers actions when conditions are met.
Agentic workflow agent
Executes multi-step tasks autonomously — researching, writing, validating, and routing — with minimal human oversight.
Internal operations agent
Automates repetitive internal tasks: report generation, data entry, cross-system updates, and approval routing.
We pick the right model for the job — not the fashionable one
We build on the full frontier stack. Model choice is driven by your use case, performance requirements, cost profile, and infrastructure constraints.
Questions about custom AI agent development
What is a custom AI agent?
A custom AI agent is an AI system built specifically around your business — your data, your workflows, your systems, and your specific tasks. Unlike general-purpose tools like ChatGPT, a custom agent knows your product catalogue, your customer history, your internal processes, and your terminology. It can take actions — not just answer questions — like updating a CRM record, raising a support ticket, sending a notification, or triggering a workflow in another system.
How is a custom AI agent different from ChatGPT or Copilot?
ChatGPT and Microsoft Copilot are general-purpose tools trained on public data. They don't know your business, your customers, or your internal systems. A custom AI agent is trained or grounded on your specific data, configured for your specific use cases, and integrated into your existing tools. It can access your CRM, your knowledge base, your order management system — and take actions within them. The result is an agent that does useful work in your context, not just a smart search box.
What can a custom AI agent actually do?
Custom AI agents can: answer complex questions from your internal knowledge base; qualify and respond to inbound leads; process and route incoming requests; monitor data sources and trigger alerts or actions; generate reports, summaries, or drafts using your data; handle customer support queries end-to-end; extract, validate, and push data between systems; and work autonomously on multi-step tasks (agentic workflows). The scope depends on what problem you're solving.
What AI models do you build on?
We build on the full frontier model stack — OpenAI GPT-4.1 and o3/o4-mini, Anthropic Claude Opus 4 and Sonnet 4, Google Gemini 2.5 Pro and Flash, and Microsoft Azure OpenAI. Model choice depends on your use case: complex reasoning tasks suit Claude or o3; fast, high-volume tasks suit GPT-4.1 or Gemini Flash; enterprise Microsoft environments often use Azure OpenAI. We recommend the right model for your specific agent — not whatever is fashionable.
What data does the agent need to be useful?
It depends on the use case. A knowledge base agent needs your documentation, policies, and FAQs. A customer-facing agent needs your product or service data. A CRM agent needs access to your CRM records. A process agent needs your workflow logic and system APIs. We scope the data requirements during the initial discovery — and design the agent to work with what you have, not require a major data project first.
How long does it take to build a custom AI agent?
A focused, well-scoped agent typically takes 2–4 weeks from kickoff to production deployment. Simple agents with clear use cases and clean data can be live in under two weeks. Complex agents with multiple integrations, custom tooling, or agentic workflows across multiple systems may take 4–6 weeks. We scope the timeline as part of the build plan, before any work starts.
How much does a custom AI agent cost?
Custom AI agents are typically priced between £10,000 and £25,000 fixed price, depending on complexity, number of integrations, and the scope of the agentic capabilities required. Simple single-use-case agents start from £10K. Multi-integration, multi-step agentic systems with custom tooling are typically £18–25K. You receive a clear fixed price before any work begins.
Can the agent improve over time as it's used?
Yes. We build feedback and logging into the agent so you can see what it's doing well and where it's falling short. Based on real usage data, we refine the agent — improving prompts, expanding knowledge, adding new capabilities. Most clients retain us on a monthly basis to continue iterating on their agent after the initial deployment.
Tell us the problem. We'll scope the agent.
Describe what your team is doing manually, or what question your business can't currently answer quickly. We'll tell you exactly what an agent could do — and what it would cost.
Get a Fixed-Price Quote