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Retrieval is the bottleneck, not the model
Most failed RAG systems failed at retrieval. We instrument retrieval first — recall@k, MRR, citation faithfulness — then choose models against that instrumented baseline.
RAG · Enterprise Search
RAG Implementation in Canada
Retrieval-augmented generation is the Canadian enterprise's most common AI use case — and the one most likely to ship a hallucination into a regulated workflow if it is not built carefully. CFRI ships RAG systems with retrieval evaluation, citation discipline, and Canadian-resident inference where the data demands it.
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Citation discipline
Every answer cites the source span the model used. If the citation is missing or wrong, the answer is suppressed. This is non-negotiable for regulated buyers.
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Canadian residency where required
We deploy on Canadian-resident infrastructure (sovereign Canadian cloud, AWS / Azure / GCP Canada regions) for data classifications that demand it, including ProtectedB design patterns for federal work.
What we deliver
- →Document ingestion + chunking pipeline
- →Vector + hybrid retrieval with eval harness
- →Citation-disciplined answer generation
- →Drift + freshness monitoring
- →Canadian-resident deployment architecture
Frequently asked
What does a RAG engagement cost?
Most production RAG engagements run six figures CAD over 8–14 weeks. Pilot validation engagements are smaller and fixed-fee.
Do you work with our existing data warehouse?
Yes. We integrate with Snowflake, Databricks, S3, SharePoint, and on-prem document stores. We do not require you to move data.
Which model providers do you use?
OpenAI, Anthropic, Google, and open-weight models depending on residency, cost, and quality requirements.
Is CFRI in the NVIDIA Inception program?
Yes — CFRI is an NVIDIA Inception member, which gives our engagements access to optimized inference stacks where it matters.
What if our content is in French?
Bilingual retrieval and answer generation is supported. We tune retrieval per language to avoid cross-language regressions.
Where to start?
Email info@cfri.io with the document corpus size and the user-facing question pattern.
Next Step
DEPLOYING RAG INTO A REGULATED WORKFLOW?
Thirty minutes with operators who have already shipped what you're trying to figure out. CAD-billed. SR&ED-aware.