Private AI Knowledge Systems for Canadian Teams
A RAG knowledge system is an AI assistant that answers from your own documents with cited, auditable sources instead of guessing. MicroPyramid builds private RAG-powered copilots, support assistants, and semantic document search for Canadian finance, public sector, legal, and SaaS teams: query your institutional knowledge in natural language, with source citations and role-based access.
Why Canadian Organisations Need Private RAG
Canadian federal departments, regulated financial institutions, and provincial health authorities cannot feed sensitive records into US-hosted AI APIs. PIPEDA's accountability principle requires organisations to take responsibility for personal information in the hands of third parties, and for many Canadian entities, that accountability requires keeping data within Canada's borders entirely.
Private RAG systems solve this cleanly. Documents are indexed and retrieved within your own environment; LLM inference runs on-premise or in AWS ca-central-1 (Canada Central). Nothing crosses jurisdictional boundaries. The architecture satisfies not just PIPEDA but also Quebec's Law 25 heightened consent requirements and BC PIPA's similar residency sensitivity, whichever regime applies to your organisation.
We've been building secure, production AI systems for 12+ years. We know that "privacy compliant" for a Canadian federal agency or a OSFI-regulated institution means more than a terms-of-service checkbox. It means auditable architecture, documented data flows, and a system that can be demonstrated to the OPC if needed. That's how we build.
What We Build for Canadian Teams
Six types of private RAG-powered knowledge systems, each shaped for Canadian regulatory requirements and data-residency obligations
Internal Knowledge Copilot
Give your Canadian team a private retrieval assistant over internal policies, SOPs, and compliance guides, with citations, role-based access, and audit trails that satisfy PIPEDA accountability principle requirements.
- Document ingestion pipeline
- Semantic retrieval with citations
- Role-based access control
AI Support Assistant
Turn your support docs, product FAQs, and ticket history into an intelligent first-line assistant, built for Canadian SaaS companies managing bilingual or multi-provincial customer bases where accurate, cited answers matter.
- Knowledge ingestion & indexing
- Retrieval-backed answers
- Fallback & escalation logic
Enterprise Document Search
Replace keyword search with semantic retrieval across contracts, regulatory filings, policy documents, and compliance records, built for the document-intensive realities of Canadian financial services, public sector, and legal industries.
- Semantic search & ranking
- Multi-format document support
- Filters & faceted navigation
Financial Services & OSC Compliance Q&A
Secure retrieval over OSFI guidelines, provincial securities regulations, internal compliance manuals, and KYC/AML policies, cited answers that reduce regulatory risk and cut compliance research time.
- Regulatory document retrieval
- PIPEDA-aligned access controls
- Audit logging
Private Document Q&A
Access-controlled Q&A over sensitive documents (client files, crown corporation records, legal briefs, and board papers) deployed in AWS ca-central-1 (Canada Central) to meet provincial data-residency requirements.
- On-premise or private cloud
- Canadian data residency (ca-central-1)
- Audit logging
Secure RAG with Citations
Every answer is attributed to its source with page-level citations, auditable, trustworthy, and safe for Canadian regulated sectors from federal public service to provincial health authorities and securities-regulated firms.
- Source-attributed answers
- Confidence scoring
- Hallucination mitigation
Where Canadian Teams Get ROI
The strongest use cases share one trait: large, growing bodies of regulated knowledge that teams need to query, without exporting data across borders
Canadian Public Sector
Knowledge systems for federal departments and provincial agencies: policy retrieval, ATIP preparation, and staff knowledge management with data residency in AWS ca-central-1 to meet Treasury Board requirements.
Financial Services & OSFI
Secure retrieval over OSFI guidance, provincial securities regulations, and internal compliance manuals, cited answers that align with PIPEDA accountability and the financial services sector's strict audit requirements.
Legal & In-House Counsel
Let Canadian legal teams and in-house counsel query matter files, regulatory guidance, and precedent libraries in natural language. Full citation trails support privilege and professional conduct obligations.
Canadian SaaS Support
Reduce support ticket volume for SaaS products with large Canadian and North American customer bases, retrieving answers from your knowledge base and escalating gracefully when confidence is low.
HR & Workforce Compliance
Help HR and people-ops teams retrieve the right provincial employment standards, benefit summaries, and policy documents instantly, reducing inconsistencies across multi-province workforces.
Sales Enablement
Fast retrieval of case studies, competitive battlecards, proposal templates, and pricing during active deals, grounded in your own data, not a generic chatbot guessing from training data.
Custom RAG, Microsoft 365 Copilot, or Glean? How to Choose
Now that Microsoft 365 Copilot is rolling out across Canadian enterprise and the federal government, the real question isn't "AI or not". It's which approach fits your data, your residency obligations, and how much you want to own. Here's the honest breakdown.
Custom RAG (what we build)
Own it outright
A private retrieval system grounded in your own documents, with page-level citations, your own access rules, and deployment in AWS ca-central-1 (Canada Central) or on-premise. You own the source code and IP: no per-seat licence, and no US CLOUD Act exposure.
Choose it when
your knowledge lives outside Microsoft 365, you need Canadian data residency or on-premise, you want answers embedded in your own product, or PIPEDA / Quebec Law 25 demands auditable citations and access control you govern.
Microsoft 365 Copilot
Productivity layer
Generative AI woven through Word, Outlook, Teams, and SharePoint. Strong when your knowledge already lives inside Microsoft 365 and generic, conversational answers are good enough for the task.
Choose it when
your content is already in M365, you accept per-seat licensing, and you don’t need custom citations, bespoke access rules, or residency guarantees beyond what the tenant gives you.
Glean
Horizontal search
A SaaS enterprise-search platform with prebuilt connectors across many tools. Useful for large organisations wanting cross-app search out of the box, accepting a third-party platform in the data path.
Choose it when
you’re a large org that wants connector-based search across many SaaS tools immediately and you’re comfortable with a vendor platform processing your index.
In practice many Canadian teams run both: Microsoft 365 Copilot for everyday productivity inside the Office suite, and a custom RAG system for the regulated, sovereign, or product-embedded knowledge Copilot can't reach. We'll tell you when off-the-shelf is the right call, including when not to hire us.
Best Fit For
- you have policies, regulatory docs, compliance manuals, or internal knowledge Canadian teams need to query quickly
- answers need citations and audit trails, fundamental to PIPEDA accountability and provincial privacy laws
- you require data residency: all data stays in AWS ca-central-1 or your own Canadian infrastructure
- you need retrieval-backed answers grounded in your own regulated data, not a public internet model
Not the Right Fit When
- you mainly need AI embedded inside an existing product workflow rather than a standalone knowledge system
- your source content is thin, inconsistent, or not yet ready to index
- you expect autonomous answers without guardrails in regulated public-sector or financial workflows
- the goal is a public-facing generic chatbot with no grounding in your own documents
If you need AI embedded inside an existing product workflow, start with AI Feature Development instead.
Related proof from our portfolio: Refactored.ai shows AI-assisted retrieval in a production learning platform, while Bough Digital demonstrates AI-powered search and recommendation at scale. See the full global service page at ai-rag-knowledge-systems.
Why Canadian Teams Work With Us
12+ years of delivery experience, shaped to fit Canadian time zones, privacy law, and CAD commercial terms
ET Mornings, Async EOD Handoffs
Eastern Time mornings overlap directly with our working hours, so morning standups and critical questions get same-session responses. End-of-day handoffs are turned around overnight, progress by the time you open Slack.
PIPEDA & Provincial Privacy Ready
We build with the OPC's accountability principle and provincial privacy sensitivity in mind: data minimisation, access controls, audit trails, and default deployment in AWS ca-central-1 (Canada Central). Quebec Law 25 and BC PIPA requirements addressed on request.
CAD Billing via Stripe
Invoiced in Canadian dollars via Stripe. No US-dollar conversion, no cross-border FX overhead, straightforward, transparent commercial terms for Canadian businesses and public-sector procurement.
Senior Engineers with Direct Access
You talk to the engineers building your system, not a project coordinator. The same senior team that ran discovery writes the code, answers questions on Slack, and shows up to sprint reviews.
How We Deliver
A focused, low-risk process designed to get Canadian teams from problem to working system fast
Discovery & Scoping
Map Canadian use cases, identify data sources, define PIPEDA / provincial privacy requirements, and set success metrics
Data Preparation
Document ingestion, chunking strategy, embedding pipeline, and vector index, hosted in ca-central-1 by default
RAG Architecture
Retrieval system design, LLM selection (private or API), prompt engineering, and context management
Build & Deploy
UI integration, accuracy testing, staged deployment, and monitoring, with full handover documentation
RAG & AI Technology Stack
We select models and infrastructure based on your Canadian data-residency, privacy, and performance requirements, not on defaults
AI & Retrieval
Data & Storage
Infrastructure
How to Get Started
We recommend a Discovery Sprint: low risk, clear output, a PIPEDA compliance review, and a foundation for everything that follows
RAG Discovery Sprint
Map your use case, assess data sources, and get an architecture and PIPEDA-aligned implementation roadmap
- Use-case mapping & data review
- Architecture recommendation
- PIPEDA / provincial privacy assessment
- Implementation roadmap
Knowledge Copilot MVP
Full build of a retrieval-based assistant with UI, source citations, and Canadian data residency
- Document ingestion pipeline
- Retrieval + LLM integration
- Web interface with access control
Ongoing RAG Expansion
Continued iteration on your AI knowledge system as your data, regulations, and use cases evolve
- Additional data sources
- Quality & accuracy improvements
- Analytics & monitoring
Client Projects & Case Studies
Products and platforms we've built for clients in Canada, UK, Australia, and worldwide over 12+ years
Refactored
AI-assisted Python learning platform with adaptive exercises and retrieval-backed tutoring at scale
See AI proof
CREDITABLE
Employee financial wellness platform for savings, loans, and workplace financial services
Read case study
Bough Digital
UK digital marketing agency, AI-powered search visibility and recommendation workflows
See portfolio
PRO Music Tutor
Premium online learning platform connecting students with world-class instructors
See more workFrequently Asked Questions
Straight answers to what Canadian founders, CTOs, and compliance leads ask before building a RAG knowledge system.
What is a RAG knowledge system?
A RAG (retrieval-augmented generation) knowledge system is an AI assistant that retrieves the most relevant passages from your own documents and uses them to generate an answer with cited sources, instead of relying on what a language model memorised from the public internet. Because every answer is grounded in your content and attributed to its source, it stays accurate, auditable, and current as your data changes, which is what makes it safe for Canadian regulated, public-sector, and financial-services work.
Can you build a RAG system with full Canadian data residency?
Yes. We deploy by default in AWS ca-central-1 (Canada Central, Montréal), with ca-west-1 (Calgary) as a second Canadian region, so your documents and embeddings never leave Canada, and we can run the entire system on-premise or in your own private cloud where a federal department or DPO requires it. Because we architect on Canadian infrastructure rather than a US-hosted SaaS, there is no US CLOUD Act exposure over your data. We build with PIPEDA, the OPC accountability principle, and Quebec Law 25 in mind from day one (data minimisation, role-based access, and full audit logging) and BC PIPA and Alberta PIPA residency sensitivity is addressed on request.
How is a custom RAG system different from Microsoft 365 Copilot or Glean?
Microsoft 365 Copilot and Glean work well when your knowledge already lives inside their ecosystem and generic answers are acceptable. A custom RAG system is the better choice when you need answers grounded in data they don’t reach, page-level citations, your own access rules, Canadian data residency or on-premise deployment, or a copilot embedded in your own product, and when you want to own the system outright rather than rent per-seat licences indefinitely. Many Canadian teams run Copilot for everyday productivity and a custom RAG system for the sovereign or regulated knowledge it can’t touch.
How do you stop the AI from hallucinating or inventing answers?
Every answer is grounded in retrieved passages and attributed with page-level citations, so a user can verify the source before trusting it. We add confidence scoring, fallback and escalation logic when retrieval is weak, and an evaluation pass on your real questions before launch, so the system says “I don’t know” or escalates to a human rather than making something up. For Canadian government, health, and financial-services teams, that auditability is the difference between a usable tool and a compliance risk.
Can it work for OSFI-regulated, federal government, or Quebec Law 25 teams?
Yes. Cited, access-controlled retrieval is a strong fit for OSFI-regulated financial institutions, securities-regulated firms, and Canadian federal and provincial public bodies: secure Q&A over compliance manuals, OSFI guidelines, policy libraries, and clinical or legal documents, with source attribution so nothing gets misquoted. Canadian data residency, audit logging, and per-team access controls are designed in, not bolted on, with awareness of federal Protected B handling and CCCS expectations. We can deliver bilingual (English and French) interfaces and retrieval to meet Quebec Law 25 and federal official-languages requirements, something most vendors in this market overlook.
You’re an offshore team. How do you handle Canadian time zones and the US CLOUD Act?
Two different concerns, and we answer both. On time zones: Eastern Time mornings overlap directly with our working hours, so morning standups and critical questions get same-session answers, and end-of-day handoffs are turned around overnight. You wake up to progress, not a blocked queue. You work directly with the senior engineers who scoped your system on Slack, not an account-manager relay, and we invoice in Canadian dollars via Stripe with no US-dollar conversion overhead. On sovereignty: because we are not a US entity and we deploy your system in AWS ca-central-1 or on-premise, your data sits under Canadian jurisdiction with no US CLOUD Act reach, and you own all the code and IP outright.
What drives the cost of an AI knowledge system?
Cost is driven by the number and messiness of your data sources, how much cleaning and chunking the documents need, your access-control and audit requirements, whether you deploy in AWS ca-central-1 or fully on-premise, whether you need bilingual EN/FR support, and how deeply the copilot integrates with your existing systems. We scope the smallest valuable version first in a discovery sprint and give you a fixed estimate in Canadian dollars before any build begins, so there are no surprises. Pricing is handled directly in conversation, not published as a one-size band.
Do we own the source code and IP?
Yes. You own all source code and intellectual property we build, committed to your repositories as we go, so there is no vendor lock-in and no per-seat platform rent if you later bring the system fully in-house. The same senior engineers who run discovery write the code and stay reachable on Slack. You are not handed off to an account manager once the build starts.
Ready to Build Your Canadian Knowledge System?
Start with a free discovery call. We'll assess your use case, your PIPEDA obligations, and your data sources, and propose a concrete first step with no obligation.