AI development company for agents and chatbots in the United States
Give customers an assistant that answers from your own content on your website or WhatsApp and passes the conversation to your team when needed. We build AI agents for businesses in the United States, starting with the questions you want to handle and the handover rules your staff need. At MSH Technologies, a studio in India, we agree the scope with you around your business and its goals.
- 250+ projects delivered
- Reviews on Google ↗
- Reply within 1 working day
Reply within 1 working day
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 agent should you build?
Start with the requests. A menu-and-button bot fits a small set of predictable choices, and its paths are easy to audit. Your team can see what each button offers and check the response. Its limitation appears when someone has a question outside the menu: they need another route to get help, or the experience can become frustrating.
An agent that answers from documents suits questions that vary when you already have the answers in writing. It needs a maintained knowledge base and tests using real questions. An answer-only agent is a lower-risk starting point; letting it change records, issue refunds or take payments adds permissions, confirmation steps and testing.
A hosted chatbot platform comes with an inbox and analytics and is quick to set up. A custom build gives you more control over data, integrations and behaviour, with more to build and maintain. We help you weigh that choice against who will use the agent: public-facing assistants need topic and tone limits, while internal assistants need document permission checks.
Rules
What AI agents in the United States need to handle
Appointment businesses need answers and booking outside opening hours. Online stores need order, delivery and returns information, with complaints and refunds passed to staff. Software companies need help-article answers and a ticket when the assistant cannot resolve a question.
For a website or online service directed to children under 13, the amended COPPA rule applies to the operator. We agree what customer data reaches the model provider, how long conversation logs are kept and who can read them, then set up the assistant around those decisions.
Where California consumer privacy requirements apply, we use AI providers that do not train on your data and limit the agent’s access to what it needs. We agree those choices with you when defining the information the assistant will handle.
How it runs
How an AI agent project runs with us
We work remotely over video calls, WhatsApp and shared project boards. IST is 10h30m ahead of Eastern and 13h30m ahead of Pacific in winter; the difference is 1 hour less during daylight saving time. Shared boards give you a place to review progress and leave feedback across that difference.
- 01
Discover
You share examples of real conversations and name an owner for each topic. We use those examples to focus the scope on questions your customers and staff actually ask.
- 02
Build the assistant
We build around your documents, the systems the agent needs to use and the points where it should hand over. You identify the sources and workflows it should cover.
- 03
Set up actions
For each booking calendar, order lookup or helpdesk tool, we define permissions and input checks with you, including whether a person must confirm an action first.
- 04
Test
We run a fixed set of real questions against agreed answers. Your staff mark wrong, incomplete or risky replies; we retest the whole set after each fix.
- 05
Launch with limits
We start with a contained audience, channel or topic. You and your team review its behaviour, and coverage widens as quality holds.
Checklist
What to have ready before we talk
Bring what you already use to answer questions and route work; it will help us agree a useful scope.
- Real questions and answersCollect common examples from emails, chats and call notes, including the replies staff give today.
- Off-limits topicsList subjects such as medical, legal or billing disputes that the agent must avoid, and what it should say instead.
- System accessHave test accounts or API access ready for the calendar, CRM, helpdesk or order database the agent will use.
- Handover routeName who receives escalations, their working hours and the message customers see when nobody is available.
- Data rulesBring your decisions on information sent to an outside AI provider, conversation-log retention and who may read the logs.
Cost & time
What affects the cost and work involved?
The scope determines how much preparation, permission design and testing the assistant needs.
Source documents
Scattered, outdated or scanned material takes more preparation than a current, organised knowledge base. The state of your content changes the work needed before the agent can answer from it.
Actions
An agent that changes something in a system needs permissions, confirmation decisions and test cases for each action. An answer-only scope avoids that action-design work.
Accuracy requirements
High-stakes or regulated topics call for larger test sets, more review and tighter limits on what the agent may say. Those choices affect the scope of testing.
Usage
Conversation volume and model choice affect the provider’s ongoing usage charges. Those charges are separate from the work of building the agent.
Avoid
Mistakes to avoid with an AI agent
Conflicting sources
An agent repeats what it is given, so different versions of a returns policy can produce different answers. Clean up the source content before launch.
A hidden route to staff
Someone stuck in a bot loop can leave or complain elsewhere. Give every conversation a clear way to reach a person.
Broad system access
Give each tool only the actions it needs, set limits on amounts, records and frequency, and log every action the agent takes.
An unclear identity
Tell people plainly that they are speaking to an automated assistant and explain what it can help with. That sets expectations before a handover.
Questions
Asked by businesses in United States
Page updated 5 November 2026
What companies develop AI chatbots?
We develop chatbots that run on your website, WhatsApp, Slack, Microsoft Teams or inside your own app. Our stack includes OpenAI, Anthropic Claude, Google Gemini, vector databases, the WhatsApp Business API and Python. The choice of components follows the channels and behaviour you agree for your assistant.
How do you stop an agent from guessing?
We ground its answers in your own content, test it against real questions and set limits so it says it does not know when an answer is missing. Keep a fixed list of questions and expected answers: without it, you cannot tell whether a prompt or model change improved the agent or made it worse.
Can you build an assistant for our internal documents?
Yes. We build internal knowledge assistants that let your team ask questions across policies, manuals and other documents. For a firm with a large document set, the build also needs permission checks so staff can find answers without seeing documents they are not allowed to access.
Who owns the content and code?
You own your domain, content and code, with no lock-in. That covers the content you bring to the assistant and the code for your project. You can discuss the assets you want included when the scope is agreed, so ownership is clear as the work is defined.
What should we review after launch?
Review conversations regularly, especially handovers and unanswered questions, to find missing content and new topics. We provide usage insights showing what people ask, what gets resolved and where to improve. Compare resolution, handover, customer ratings and staff time with the period before launch, and rerun the evaluation set after changes.
When does the agent pass a conversation to a person?
You set the handover points with us. They might include low confidence, a complaint, a refund or a direct request to speak to someone. We also define what context the staff member receives, then test the agent against real questions and set limits on what it can say and do.
Tell us what you need
Sohail, Founder, replies within 1 working day (Mon–Sat, IST). Free and no obligation.
Also in United States