AI Agent Development for Real Business Workflows
An agent is only useful when it can safely take action in your systems. We build agents with clear tools, guardrails and hand-off points — for chat, voice and phone.
Discuss your AI projectThe problem
01 — ContextGeneric agent frameworks make it easy to wire an LLM to tools and hard to predict what it will do next.
In real workflows — taking an order, updating a CRM, booking a slot — an agent that improvises is a liability.
The approach
02 — MethodWe design the workflow first, then give the model a narrow set of well-typed tools and explicit states it moves between.
Every action is logged, risky steps require confirmation, and there is always a path to a human.
What we build
03 — CapabilityVoice and phone agents
Inbound and outbound calling agents using telephony APIs and speech models.
Tool-using assistants
Agents that read and write to your CRM, database, calendar or internal APIs.
Multi-step workflow agents
Agents that plan and execute defined processes with checkpoints.
Internal team agents
Assistants that work with your team's codebase, documents and tools.
Use cases
04 — Applications- Phone ordering for restaurants
- Lead qualification calls
- CRM data entry from conversations
- Internal support assistants
Typical architecture
05 — SystemProcess
06 — DeliveryUnderstand
Understand the business problem and the outcome you need.
Architect
Choose the AI architecture, integrations and technical approach.
Prototype
Validate the critical workflow before building around it.
Build
Develop the product in milestones you can review.
Validate
Test quality, performance, reliability and edge cases.
Launch
Deploy the production system and monitor it.
Improve
Optimise using real usage and feedback.
Questions
07 — FAQTell us what you want to build.
Send a short brief. We'll reply personally with questions or a suggested next step — usually a technical discovery call.