AI automation agency for agents and chatbots in Canada
Give customers an automated assistant that answers questions from your content, looks up orders and books appointments. For your business in Canada, we build agents that read a message, find an approved answer and respond or take an action in a connected system. We start by learning about your business and agreeing the scope with you before building.
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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 ask. A menu-and-button bot suits a small set of predictable requests, and its paths are easy to audit. Someone whose question falls outside those paths will have a harder time getting an answer. An agent that searches documents suits a wider range of questions when the answers already exist in writing; your team will need to maintain those sources and test the answers against real questions.
A hybrid design combines buttons for structured tasks such as booking or order status with AI for questions people write in their own words. A person remains available behind both routes. This suits a support desk handling a mixture of routine requests and unusual enquiries, where a fixed menu alone would leave gaps.
You also have a platform decision. A hosted chatbot platform includes an inbox and analytics and takes less setup work. A custom build gives you more control over data, integrations and agent behaviour, while leaving more for your team to build and maintain. Compare those trade-offs against the systems and controls you need before choosing.
Rules
What a chatbot project in Canada has to handle
Appointment businesses need answers to common questions and a way to book, move or cancel appointments outside opening hours. Software companies need help-article answers and a ticket with the details when first-line support cannot resolve a request. Choose the first task around the enquiries your staff actually receive.
For private-sector commercial activity, PIPEDA sets federal rules on collecting, using and disclosing personal information; Alberta, British Columbia and Quebec have their own substantially similar private-sector privacy laws. Where those rules apply, the build needs decisions about the information sent to an AI provider, log retention and who can read conversations. We set up limited agent access and use providers that do not train on your data.
How it runs
How an agent or chatbot project runs with us
We work remotely over video calls, WhatsApp and shared project boards. India is 9h (Newfoundland) to 12h30m (British Columbia, Yukon) ahead in winter, so we use the shared board to keep decisions and work visible across the time difference.
- 01
Discover
Share a sample of real conversations and name an owner for each topic. We use those examples to focus the scope on questions that actually reach your team.
- 02
Build and review
We connect the approved sources and write the agent’s instructions and limits. You review draft answers for accuracy and tone before anyone outside your organisation sees them.
- 03
Test
We test the agent against real questions and check the limits on what it can say and do. Your examples give the testing work a practical basis.
- 04
Launch with a limit
Start with staff, a single channel or a single topic. That exposes real behaviour while keeping mistakes contained; coverage widens as the quality holds.
Checklist
What to have ready before we talk
For an internal knowledge assistant, bring the material your team would use to answer questions.
- Real enquiriesCollect common questions and the answers staff give today from emails, chats and call notes.
- Approved sourcesGather FAQs, policies, price lists or manuals, and name someone responsible for keeping each current.
- Excluded topicsList subjects the agent must not handle, such as billing disputes, and what it should say instead.
- System accessIdentify test accounts or API access for the booking calendar, CRM, helpdesk or order database.
- Data rulesBring your internal rules for external AI providers, conversation retention and access to logs.
Cost & time
What affects the cost and work involved
The scope determines how much preparation, connection work and testing the agent needs.
Source material
Scattered, outdated or scanned documents need more preparation than a tidy, current knowledge base.
Connected systems
Each system adds integration work; a documented API gives the build a different starting point from a system that needs a workaround.
Actions and permissions
A booking or order lookup needs its own permissions and input checks, plus a decision on whether a person confirms first.
Ongoing usage
Conversation volume and model choice set the model provider’s usage charges, which are separate from the build cost.
Avoid
Mistakes to avoid when building an agent
Conflicting sources
An agent repeats what it is given. Remove outdated versions and settle conflicting policies before connecting the documents.
An unsettled process
If staff disagree on how bookings or refunds work, settle the process before asking the agent to follow it.
A hidden route to staff
Someone stuck in a bot loop can leave or complain elsewhere. Give every conversation a clear route to a person.
An unclear identity
Say plainly that the assistant is automated and explain what it can help with, so people know what to expect at handover.
Questions
Asked by businesses in Canada
Page updated 5 November 2026
Which companies develop AI chatbots?
Among the companies building AI chatbots, MSH Technologies is a web, app and AI development studio in India. Our agent stack includes OpenAI, Anthropic Claude, Google Gemini, vector databases, the WhatsApp Business API and Python. An agent can run on your website, WhatsApp, Slack, Microsoft Teams or inside your app.
What does an AI agent cost?
There is no fixed price: the work depends on what the agent answers and what it is allowed to do. Grounding answers in your content takes preparation, while actions that change records, issue refunds or take payments need tighter permissions, confirmation steps and more testing. Agreeing those boundaries makes the scope clearer.
What happens when the agent cannot help?
The agent hands the conversation to your team according to rules we set. Those rules can cover low confidence, complaints, refunds or a direct request to speak to a person. We also define what context the staff member receives, so the handover includes information from the conversation.
Who owns the work we receive?
You own your domain, content and code, with no lock-in. Ask us to identify those assets in the agreed scope so your team knows what it will receive and who will manage each part after launch. Ownership also gives you control over the content your agent uses.
How do we know if the agent is useful after launch?
Review what people ask, what gets resolved and where answers need improvement. We provide usage insights for that review. You can also compare resolution and handover rates, customer ratings and staff time saved with the period before launch. Review a sample of conversations, especially handovers and unanswered questions, to spot missing content.
How do you limit made-up answers?
We ground the agent’s answers in your own content and set limits so it says it does not know when an answer is missing. Keep a fixed set of questions and expected answers to check changes. Rerun that set after changes to prompts, documents or the model version, since a fix in one area can break another.
Tell us what you need
Sohail, Founder, replies within 1 working day (Mon–Sat, IST). Free and no obligation.