inparlor.
Canada

AI Chatbots & AI Agents.

Chatbots, AI agents, and RAG assistants that ship to production, not demos.

Pricing

Custom quote — proposal within 48 hours

fixed project

Indicative CAD conversion; final quotes are issued in CAD against itemised scope.

Why Canada buyers choose us

A US-headquartered software team building for Canadian companies — same-timezone collaboration, CAD invoicing, and PIPEDA-aware data handling from the first call.

  • US-headquartered team working ET/PT overlap hours with clients from Halifax to Vancouver — no overnight handoff gap
  • Invoicing in Canadian dollars (CAD), so budgets, change orders, and retainers stay in one currency
  • PIPEDA-aware data handling, with provincial-residency and access-request requirements scoped into every build
  • Quebec Law 25 awareness for Montreal and other Québec-based clients handling personal information
  • Senior engineers on every engagement — your product is never staffed to whoever is free that week

We handle Canadian personal information under PIPEDA, scoping consent, breach-notification, and data-residency expectations into the architecture rather than bolting them on later. For Québec-based clients we factor in Law 25 (the modernized Act respecting the protection of personal information in the private sector).

What this includes

Deliverables, line by line.

  • Scoping doc that names the one workflow AI will actually improve
  • RAG pipeline over your documents with source-cited answers
  • Chatbot or in-product assistant wired to your data and actions
  • Agent design with defined tools, action boundaries, and approval steps
  • Eval suite that scores accuracy before and after every change
  • Guardrails for prompt injection, PII, and off-topic responses
  • Vector store setup in pgvector or Pinecone
  • Streaming UI built on the Vercel AI SDK
  • Cost and latency monitoring per feature
  • Fallback and human-handoff paths for low-confidence answers, with source code and prompts in your GitHub org
Process

How an engagement runs.

  1. 01

    Use-case scoping

    One week. We separate the chatbot and agent ideas worth building from the ones that sound good in a meeting. You leave with a scoped feature, a cost estimate per request, and a definition of done that is measurable.

  2. 02

    Data and retrieval

    We ingest your documents, chunk and embed them, and stand up retrieval so answers are grounded in your data, not the model's memory. Every answer can cite its source.

  3. 03

    Build and integrate

    We wire the chatbot or agent into your product with streaming responses, the right model per task, and the actions it is allowed to take. You demo it in your own app, not a sandbox.

  4. 04

    Evals and guardrails

    We build a test set of real questions with known-good answers and score every change against it. Guardrails catch injection, PII leakage, and out-of-scope requests before launch.

  5. 05

    Production rollout

    Feature-flagged launch to a small cohort, with cost and latency dashboards live from day one. We tune prompts, retrieval, and agent behaviour against real usage before expanding.

FAQ

What buyers ask before signing.

Ready to start?

Ready to start with AI Chatbots & AI Agents?

Tell us about your business and current numbers. We respond within 48 hours with scope, pricing in CAD, and timeline.

Get a proposal