Specialised and orchestrated
Specialised agents routed through a shared provider registry, so each job goes to the agent, and the model, suited to it.
Services
AI agent development and multi-agent automation
AI agents designed, built, and deployed to automate complex workflows inside your systems. Production-grade, not prototypes. Audit trails, compliance logging, human-in-the-loop where required. Built on LLMs, integrated with your existing stack.
Most teams we talk to are stuck between prototype and production. The demo worked, the board is asking about AI strategy, and the path from there to something customers or staff rely on daily is unclear. That gap is exactly where we work.
- Single agents or a coordinated team of them, each owning a job
- Every action logged: you can always see what an agent did and why
- The advisory and the build come from the same engineers
25+ years of production delivery, including regulated financial services.
Production-grade delivery, not prototypes or slide decks.
Secure-by-default. ISO 27001 advisory capability.
Direct access to the senior people who do the work. No account managers.
Multi-agent automation
A team of agents alongside your team
Not one chatbot. A set of specialised agents, each owning a job: triaging the inbox, chasing invoices, preparing reports, keeping systems in sync. They pick work up, carry it through your systems, and post the result back where your team already looks.
Your staff stay in charge. Agents escalate what they should not decide, every action is logged, and headcount conversations become about growth instead of keeping up.
- Specialised agents orchestrated through a shared registry
- Human approval on the decisions that matter
- Cost visible per agent, per task, per user
How we build
Production multi-agent systems built end to end, with the operational rigour that separates a demo from something your business runs on.
Schema-validated outputs
Every output is validated against a schema before it touches your systems. Malformed answers are retried, not written.
Retryable background jobs
Agent invocations run as retryable background jobs: failures recover on their own instead of paging a person at 2am.
Model matched to task
Model choice is matched to task complexity and cost. Multi-provider is the default, based on production experience rather than benchmarks.
Cost attributed per user
Spend is tracked and attributed per user and per task, so the finance question always has a real answer.
Audit and compliance logging
Decisions carry an audit trail and compliance logging, proven in regulated financial services environments.
Engagement shapes
- 01
AI strategy workshop
1 to 3 days: figure out what's worth building, and what isn't.
- 02
Roadmap and architecture
2 to 4 weeks: scope the work, design the system, de-risk the build.
- 03
Agent or RAG proof of concept
4 to 8 weeks: something real to learn from, built to graduate into production.
- 04
Production build
6 to 12 weeks: take it live, with the operational rigour above.
- 05
Ongoing AI advisor
A few hours a week: a senior AI voice inside your team.
Track record
Live in production
Multi-agent systems
Multi-agent systems designed and run to carry real work end to end - from writing and shipping software to operating the day-to-day workflows a business runs on. Fully independent or human-in-the-loop, proven in production.
- AI agents
- multi-agent architecture
- LLM orchestration
JustPayMe
A multi-agent platform that handles payments, scheduling, quoting, and client relationships for small businesses, giving a plumber or a tutor the same back-office capability as a large company, so they can focus on their work.
- AI agents
- payments
- SME fintech
Business process agents
AI agents that slot into the roles businesses already run - scrum masters, payment processors, customer service handlers, and more. We've deployed these inside regulated environments where reliability and auditability aren't optional.
- AI agents
- business automation
- regulated environments
Client feedback
What clients say.
“Tech Studio provided a first class technical build and support service for our clients' online design projects.”
“I have been very happy with Tech Studio's services in the last 4 years. All of my problems had been resolved quite promptly and with patience. They have been the best so far.”
“Very skilled, and willing to help and go the extra mile. Highly recommended.”
“Have been extremely impressed with the service provided and support when required.”
AI agent questions
What is an AI agent, and how is it different from a chatbot?
A chatbot answers. An agent acts: it reads the request, looks things up in your systems, makes or requests a decision, and carries out the next step. A multi-agent system is a set of them, each specialised, coordinating on real workflows.
What tasks can agents actually take on?
The work that is frequent, rule-shaped, and currently eats skilled people's time: inbox triage, invoice chasing, report preparation, data reconciliation, customer replies, scheduling. If you can describe how a good employee does it, an agent can usually carry most of it.
How do agents work alongside our staff?
Agents own the repetitive middle; people own the judgement. Anything outside an agent's remit escalates to a named person with full context, and your team can watch, correct, and tighten what agents are allowed to do over time.
What does it cost compared to hiring?
An agent is scoped and priced as a fixed build, then runs for a fraction of a salary. More usefully: the pilot phase gives you a per-task cost from real usage, so the comparison is arithmetic, not faith.
What can agents access, and is our data safe?
Agents get the narrowest access that does the job, through controlled integrations, in your accounts wherever possible. Every read and write is logged. We are comfortable in front of security reviews; the approach was shaped in regulated environments.
What happens when an agent gets something wrong?
The same as with a person, minus the ambiguity: the audit trail shows exactly what happened, the action is corrected, and the agent's rules or thresholds are tightened. Accountability stays with named humans; agents never get blame or excuses.
Related services
AI Implementation
Practical AI implementation: automate the processes that eat your team's week, with measurable results.
WhatsApp Business Agents
Official WhatsApp Business Platform setup plus an intelligent agent, from receptionist to taking real action.
Intelligent Chatbots
Conversational agents on WhatsApp, Slack, or Teams that answer, act, and hand off to a person cleanly.
Blog
Related guides
More on this from our blog.
Get in touch
Book a call
Thirty minutes on where you are with AI and where you want it to be. If we can help, we will propose a shape. If the honest answer is that you do not need this yet, we will say so.
