AI Internal Operations That Give Your Team 10× Capacity Without 10× Headcount

We use Claude (Anthropic) for document analysis, policy Q&A, and complex reasoning tasks — it excels at following nuanced instructions and maintaining context across long documents. We use GPT-4 for structured data extraction and report generation. We use specialised models (Whisper for audio, Vision models for document images) where appropriate. Model selection is always task-specific.

We build AI systems that process data within your existing security boundary — using API calls to AI providers with data processing agreements, or deploying models on-premises for the most sensitive data. We never store sensitive internal data in external AI platforms beyond the API request. Data handling architecture is defined and documented before build begins.

We use shadow-mode testing — running AI automation in parallel with humans for 2–4 weeks, comparing outputs, and measuring error rates before full handoff. For high-stakes tasks (financial reporting, legal review), we maintain human oversight as a final check. We only fully automate tasks where AI error rates are below defined thresholds.

Yes — agentic systems that execute multi-step tasks without human intervention are a core capability. These are built with appropriate safeguards: explicit scope boundaries, logging of every action, human escalation triggers for edge cases, and rollback capability. Full autonomy is introduced incrementally as confidence is established.

Time savings are visible immediately — typically in the first week as high-volume automations deploy. Financial ROI (cost per task reduction, FTE capacity reclaimed) is typically calculated at the 60-day mark when volumes are sufficient for accurate measurement.

Yes — every deployment includes documentation and training for the team members who interact with the AI systems. We design for maximum adoption: AI outputs delivered in the tools people already use (Slack, email, Notion) rather than requiring login to a new platform.