Most AI you can buy off the shelf is a chat window. It cannot read your CRM. It cannot trigger your workflows. It cannot reason across your real operating context. So the value caps out quickly. The work that would compound stays locked behind APIs nobody has the bandwidth to wire up.
Teylu builds custom AI agents on the Claude Agent SDK and the Model Context Protocol that solve this properly. Agents that read your systems, reason against your real data and take action across the tools your business already runs on. The result is an AI layer that does work, not just answers questions.
What you get:
Generic AI assistants are great at the first hundred prompts. They hit a ceiling the moment the work needs to span systems, hold state across steps, take an action in production or be governed for compliance. Most businesses live above that ceiling. Custom agent development is how you get past it.
The Claude Agent SDK is Anthropic's production framework for serious agent work. It handles tool use, multi step reasoning, context management and safety in the way real production demands. We build on it because the result is reliable, governable and supportable rather than experimental.
MCP is the open protocol Anthropic created for connecting AI models to external tools and data. It is becoming the default standard, with adoption now across Anthropic, OpenAI and Google. We build custom MCP servers that connect Claude to the systems your business actually runs on, with permissions, audit and governance built in.
Sales operations agents that triage and enrich leads. Customer support agents that resolve common queries against your knowledge base. Marketing operations agents that run campaign QA and report assembly. Finance agents that draft commentary and flag exceptions. Research agents that consolidate intelligence across sources. Anywhere the work needs reasoning plus action, an agent is the right shape.
Our agents do not live in a notebook. They live in production, hooked into your systems, running every day, with monitoring, audit and human checkpoints designed in. The difference between a demo and a deployed agent is the work most builders skip. We do not skip it.
Where your business runs on a bespoke system, an internal database or a SaaS without a standard MCP server, we build the integration. The custom MCP server gives Claude controlled, audited, permission aware access to the system. The agent reads, reasons and acts within the rules you set.
Not every action runs autonomously. Where a decision needs human sign off, the agent surfaces it with full context for a fast review. The senior team stays in control of the calls that matter without being dragged into the routine work that does not.
Every agent action is logged. Every tool call is auditable. Every decision is explainable. The agent has a documented model card, a defined acceptable use scope and a clear EU AI Act categorisation. Your governance, risk and procurement teams get the documentation they need to sign off.
Triage inbound, enrich accounts, score leads, draft follow ups, schedule meetings, flag account changes. The sales operations layer stops being a manual chase and starts being an intelligent assistant working ahead of the team.
Brief intake, campaign QA, audience segmentation, performance commentary, lifecycle send coordination, attribution reconciliation. The agent handles the routine, the team handles the strategy.
Resolve common queries against your knowledge base, route complex issues with full context, draft responses for human review, surface churn risk. Time to resolution drops, escalations to senior team members drop, customer experience lifts.
Draft monthly commentary, flag exceptions in transactions, prepare board paper sections, summarise contracts, monitor supplier performance. The finance and operations functions get a working assistant rather than another reporting layer.
Consolidate competitive intelligence, monitor market signals, prepare account research briefs, summarise sector developments. Senior team members get the inputs they need without the search and copy paste tax.
Where the work is unique to your business and not covered by a generic category, we design a custom agent for that exact process. The Claude Agent SDK plus MCP gives us the flexibility to build for the operating model rather than bend the operating model around a tool.
You get a properly architected agent layer that integrates cleanly with your systems, documents its behaviour and respects your security posture. No shadow integrations. No undocumented data flows. No surprises in the next pen test.
You get a working production agent shipping value inside the operating model. The commercial case is measured against the work the agent does, not the impressive demo it once delivered.
The deployment runs on Claude through AWS Bedrock UK South for UK data residency. Personal and sensitive data flows are minimised. Audit trail is clean. EU AI Act categorisation and ICO AI Code of Practice alignment are designed in from day one. The 2 August 2026 high risk obligations are factored in.
Agents have scopes. They have permissions. They have human checkpoints. They have audit. They are configured to fail safely rather than fail catastrophically. Safety is the work of building production agents, not an afterthought.
General development teams write code. They do not always understand AI safety, agent design patterns or the operating model considerations that distinguish a working agent from a flashy demo. Teylu builds with Anthropic's production framework, in line with Anthropic's safety principles.
Agent platform vendors give you a no code interface and a ceiling. Real production agents need real configuration: custom MCP servers, bespoke tool use, custom evaluation, governance integration. We build for production, not for the vendor demo.
Six to twelve weeks from discovery to a production agent. Phase one scopes the agent and designs the architecture. Phase two builds the agent, the MCP integrations and the governance documentation. Phase three deploys, tunes and embeds with the team.
Fixed scope build, then ongoing retainer for agent maintenance, capability extension and evolution as Anthropic ships new SDK and MCP capabilities.
See the custom agents Teylu has shipped into production for marketing, sales, operations and finance teams across the UK.
This is built for businesses where off the shelf AI has hit a ceiling and the next lift needs an agent that integrates into the systems and the work. That usually means:
Scaling B2B businesses wanting to lift sales, marketing or customer success operations beyond what generic AI tools can deliver.
Technology and product leaders wanting a properly architected, governed agent layer rather than a wild assortment of shadow integrations.
Operations and finance leaders with routine high volume work that needs intelligent automation rather than dumb scripting.
Traditional UK businesses with bespoke systems that no off the shelf AI integrates with cleanly.
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Week 1 to 2
We document the work, the systems involved, the data flows and the human checkpoints. We design the agent architecture, the MCP integration plan and the governance model.
A documented agent specification, an integration architecture and a governance model. Sign off before any code is written.
Week 2 to 8
We build the agent on the Claude Agent SDK, write the custom MCP servers, integrate with your systems and configure the human checkpoints. We test against real work.
A working agent integrated into your systems, tested against real work and ready for staged rollout.
Week 8 to 10
We deploy into production, deliver the governance documentation, train the team on oversight and audit, and embed the agent into the operating model.
A production agent shipping value daily. A team that knows how to oversee and intervene where needed. A documented governance posture your risk and security teams can sign off.
Week 10 onwards
We tune the agent against early use, extend its capability where the work demands and bring in new SDK and MCP capabilities as Anthropic ships them.
An agent that compounds in value as it runs longer, an operating model that benefits from it and a team confident in extending the work themselves.
Tell us about the work, the systems and the operating model. We will tell you whether a custom agent is the right next move.
Three tiers, sized to the complexity of the agent.
Agent Scoping (entry tier)
A two week scoping engagement covering architecture, integration design and governance, with a written specification and build estimate.
Implementation (core tier)
Six to twelve week build of the agent, the MCP integrations, the governance pack and the team rollout. Senior Teylu engineers and architects embedded throughout.
Embedded AI Labs (ongoing tier)
Monthly retainer to tune, extend and evolve the agent as Anthropic ships new SDK and MCP capabilities.
Pricing is transparent, sized to the integration complexity and the operating risk.
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Our team builds with the Claude Agent SDK and MCP every day. The agents and integrations behind our client work for HMS Networks, Arrow ECS, Timberplay and TouchWood Play are built with the same patterns we would bring to your build. The work is shipping, not theoretical.
If off the shelf AI has hit a ceiling for your business and the next lift needs a properly built agent, this is built for you.
Speak to a senior member of the team. We will scope a discovery in the call and give you a clear next step.
What is the difference between an AI agent and a chatbot?
A chatbot answers questions in a window. An agent reads your systems, reasons about the work, takes actions through tools and operates over multiple steps with human checkpoints where they matter. Agents do work. Chatbots answer questions.
What is MCP and why does it matter?
The Model Context Protocol is the open standard for connecting AI models to external tools and data. We build custom MCP servers where standard ones do not exist, with permissions, audit and governance built in. The result is a maintainable, governable integration layer.
How is this safe to put in production?
Agents have scopes, permissions, human checkpoints and audit. They are configured to fail safely rather than catastrophically. EU AI Act categorisation and ICO alignment are built in. Safety is the work of building production agents, not an afterthought.
What kinds of work do you build agents for?
Sales operations, marketing operations, customer support, finance and operations, research and intelligence, bespoke processes unique to your business. Anywhere the work needs reasoning plus action, an agent is the right shape.
How long does it take to build?
Six to twelve weeks from discovery to a production agent. Phase one scopes and designs. Phase two builds the agent and the MCP integrations. Phase three deploys, tunes and embeds with the team.
Have a question we have not answered? Tell us. We will give you a straight answer, not a pitch.
