AI development company in London for agents and chatbots
You get an AI agent or chatbot built to answer customer questions, book appointments and pass conversations to your team when needed. For your London business, we use your own content for answers and connect the actions you want the agent to take. We are a web, app and AI studio in India, and we work with you on the scope and build.
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What happens next
- 01Tell us what you need, in the form or on WhatsApp.
- 02Sohail replies within 1 working day (Mon–Sat, IST).
- 03We agree the scope together, then send your quote.
- Projects delivered
- 0+Projects delivered
- Years building for the web
- 0+Years building for the web
- Live and in use
- 0%Live and in use
What you get
What’s included in AI agents & chatbots
Customer support agents
Answer questions on your website and WhatsApp using your own content.
Internal knowledge assistants
Let your team ask questions across policies, manuals and documents.
Action-taking agents
Book appointments, create tickets, look up orders and update records.
Human handover
Clear rules for when the agent passes a conversation to your team.
Guardrails & testing
Agents tested against real questions, with limits on what they can say and do.
Usage insights
See what people ask, what gets resolved and where to improve.
Tools we use: OpenAI, Anthropic Claude, Google Gemini, Vector databases, WhatsApp Business API, Python.
Choosing
Which kind of chatbot should you build?
Start with the questions people actually ask. A menu-and-button bot suits a small set of predictable requests: its choices are easy to audit, but someone with a question outside the menu can get stuck. An AI agent that answers from documents is a better fit when questions vary and the answers already exist in writing. It needs a maintained knowledge base and tests against real questions.
A hybrid design uses buttons for structured tasks such as booking or order status, with free-text AI answers for other questions and a person behind both routes. It suits a support desk that handles routine requests alongside unusual ones.
You also have a platform decision. A hosted chatbot platform is quick to set up and comes with an inbox and analytics. A custom build gives you more control over data, integrations and behaviour, with more to build and maintain. Choose according to the control you need and the work your team can maintain.
Local
What London organisations need from an agent
London has a concentration of technology companies in East London Tech City. For a software company, a support agent can answer from help articles and open a ticket with the relevant details when it cannot resolve a question.
Tourism is a major industry in London. Travel and hospitality businesses receive enquiries at night and at weekends, so an agent has a practical job to do when a reply would otherwise wait until morning.
London also has universities and colleges. An organisation with a large collection of policies, manuals or contracts could use an internal assistant to help staff find answers, with permission checks on the documents each person may access.
Rules
Handling customer data in the United Kingdom
UK data protection includes the UK GDPR and the Data Protection Act 2018, so customer data needs a place in the build discussion. We set limits on what the agent can access and use AI providers that do not train on your data. We also plan what information reaches the provider, how long conversation logs are kept and who can read them. These decisions shape the agent and its connections before customer conversations begin.
How it runs
How an agent project runs with us
We work remotely over video calls, WhatsApp and shared project boards. IST is 5h30m ahead of the UK, or 4h30m during British Summer Time, so shared boards keep decisions and feedback visible across the time difference.
- 01
Discover
We learn about your business, audience and goals, then agree the scope with you. You share feedback as designs are refined before code is written.
- 02
Gather examples
You share a sample of real conversations and name an owner for each topic, so the scope reflects the questions your team receives.
- 03
Build and review
We connect the sources and write the agent’s instructions and limits. You review draft answers for accuracy and tone before people outside your team see them.
- 04
Test
Staff check answers against an agreed set of real questions, mark wrong or risky replies, and retest the whole set after each fix.
- 05
Launch with limits
Start with staff, a single channel or a single topic. Widen coverage as the quality holds.
Checklist
What to have ready before we talk
Bring the material your team uses to answer and act on enquiries.
- Common questions and current answers from real emails, chats and call notes.
- FAQs, policies, price lists or manuals the agent may use, with an owner to keep each current.
- Test accounts or API access for systems such as your calendar, helpdesk or order database.
- A handover routewho receives conversations, when they are available and what customers hear outside those hours.
- Your rules for data sent to AI providers, conversation log retention and access to logs.
Cost & time
What affects the cost and time involved
The work depends on your sources, connections, testing needs and expected use.
Source documents
Scattered, outdated or scanned material needs more preparation than a tidy, current knowledge base.
System connections
Each connection adds work; a documented API gives us a clearer route than a system that needs a workaround.
Accuracy requirements
High-stakes or regulated topics call for larger test sets, more review and tighter limits.
Conversation volume and model choice
These affect ongoing model-provider usage charges, which sit separately from the build.
Avoid
Mistakes to avoid with AI agents
Conflicting sources
An agent can repeat conflicting policies. Clean up old versions before launch and keep the approved source current.
An unsettled process
If staff disagree on refunds or bookings, agree the process before asking an agent to follow it.
A hidden route to staff
Give customers a clear way to reach a person, so they are not trapped in a bot conversation.
Broad system access
Restrict each tool to the actions needed, limit amounts, records and frequency, and log every action.
Questions
Asked by businesses in London
Page updated 5 November 2026
What companies develop AI chatbots?
We build AI agents for customer conversations and internal teams. At MSH Technologies, our agent stack includes OpenAI, Anthropic Claude, Google Gemini, vector databases, the WhatsApp Business API and Python. The useful choice is the one that fits your content, systems and handover needs.
Where can our agent run?
An agent can run on your website, WhatsApp, Slack, Microsoft Teams or inside your own app. Choose a channel where the intended users already ask questions: a customer support agent and an assistant for your own staff do not have to use the same channel.
How do you stop the agent guessing?
We ground its answers in your own content, test it against real questions and set clear limits. When the answer is missing, the agent is instructed to say it does not know instead of guessing. That also gives your team a clear signal that the source content needs attention.
Can an agent take action in our systems?
Yes. An action-taking agent can call tools such as a booking calendar, order lookup or helpdesk. Each connection needs its own permissions and checks on the information supplied to it. You also decide whether a person should confirm an action before the agent carries it out.
Should we build for customers or for our own team?
Choose according to who needs the answers and which documents they are allowed to see. A customer-facing agent needs tight limits on its topics and tone. An internal assistant needs permission checks, so staff can only retrieve information from documents they are authorised to access.
What happens after the agent launches?
We provide usage insights showing what people ask, what gets resolved and where to improve. Review a sample of conversations, especially unanswered questions and handovers, and compare measures such as resolution and staff time with the period before launch. Rerun the evaluation set after changes to prompts, documents or the model.
Tell us what you need
Sohail, Founder, replies within 1 working day (Mon–Sat, IST). Free and no obligation.
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