01
AI Discovery & Use-Case Mapping
We run structured workshops with stakeholders who touch customer and internal communication daily—support, legal ops, product, HR policy—to chart where large language models add value and where they introduce risk. Deliverables include a prioritized use-case backlog, data-flow sketches showing which systems hold source truth, and a pilot recommendation with effort ranges. We document integration points for Copilot, custom RAG stacks, or hybrid approaches so leadership can compare options without vendor slide decks. Discovery ends with a go/no-go brief you can share with your board or IT security team.
02
Grounded Assistants & RAG
We design retrieval-augmented generation pipelines that pull from your wikis, PDF libraries, ticket exports, and CRM knowledge bases before the model drafts a reply. Chunking strategy, metadata filters, and citation formatting are tuned so reviewers can trace every sentence. We benchmark against your existing search and measure hallucination rates on a client-provided evaluation set. Pilots ship with logging, feedback capture, and a re-indexing schedule tied to document owners. Suitable for internal help desks, partner portals, and controlled customer-facing assistants where accuracy matters more than creative flair.
03
Content Operations & Documentation
An assistant is only as current as the material it retrieves. We audit documentation estates for duplication, orphaned pages, and conflicting versions—then propose ownership models, update cadences, and plain-language templates that staff will maintain after we leave. Where appropriate, we introduce AI-assisted drafting workflows with mandatory human edit steps, style guides tuned for Canadian English, and tagging schemas that improve retrieval quality. This service pairs naturally with RAG deployments and reduces the “garbage in, confident garbage out” failure mode that sinks many LLM rollouts.
04
Customer Support Copilots
We build agent-assist and tier-one customer flows that suggest replies grounded in your macros, policy library, and resolved ticket history. Tone guides keep language aligned with brand voice; refusal rules block categories that require licensed advice or live escalation. Integrations with Zendesk, Intercom, Salesforce Service Cloud, or custom stacks are scoped during discovery. We measure handle time, first-contact resolution, and reviewer override rates so you know when automation helps agents versus when it creates rework. PIPEDA-aligned consent and retention settings are documented for customer-facing channels.
05
Responsible-AI Guardrails
Before production traffic hits an assistant, we implement classification layers, prompt boundaries, output filters, and escalation triggers aligned to your risk appetite. That includes PII redaction patterns, topic blocklists for regulated advice, logging for audit, and incident playbooks when a model oversteps. We align with your existing privacy impact assessment process and supply language for internal acceptable-use policies. Guardrails are tested with adversarial prompts and edge cases drawn from your real support transcripts—not generic benchmark sets alone.
06
Team Enablement
Technology without adoption is shelfware. We train prompt reviewers, documentation owners, and frontline staff to work with grounded assistants confidently— including when to override, how to flag bad retrievals, and how to submit corrections that improve the index. Sessions cover LLM limitations in plain language, hands-on exercises with your pilot environment, and office hours during the first month of rollout. Enablement materials stay with you: runbooks, reviewer checklists, and metrics dashboards your ops team can maintain without ongoing dependency on external developers.
