Welcome to January’s edition of Dura Digital’s newsletter. This month, see how Dura Digital’s compliance agent in Microsoft Copilot Studio delivers cited, step-by-step answers inside Teams and M365 Copilot, why winning with AI in 2026 requires redesigning products and customer journeys around outcomes and governance, and how Prompt Reverse Engineering turns bad outputs into better prompts. We also cover a platform approach to RAG that strengthens ingestion, retrieval, grounding, and observability for reliable, production-ready systems.
Dura Digital's AI Agent for legal compliance
Dura Digital’s compliance agent, built in Microsoft Copilot Studio, turns manuals and PDFs into cited answers and step-by-step guidance inside Teams and M365 Copilot. Grounded in curated knowledge, structured instructions, and simple routing, it accelerates chat-based Q&A for HR, onboarding, product manuals, and other documentation-heavy workflows. Is your team drowning in legal compliance work? Give them the super-power of an AI agent!
Re-imagine products and customer experience with AI
AI has shifted from being a differentiator to infrastructure, rewarding teams that redesign workflows, customer journeys, and decision-making processes rather than layering features on top. The priority in 2026 is outcomes and governance: clear strategy, recoverable agent actions, strong ontology, provenance, and curation over volume.
Turn bad model outputs into a debugging signal with Prompt Reverse Engineering. Identify the defect behind factual errors, missing steps, format drift, or role drift, then apply targeted patches and keep a simple changelog to make prompts reliable without bloating them.
Retrieval-Augmented Generation (RAG) succeeds at scale only when treated as a platform, not a feature. The winning approach is a layered architecture that fixes ingestion and metadata first, uses hybrid retrieval with filters, and adds grounding, validation, and observability. With those foundations, agentic RAG can iterate on queries and escalate when confidence is low, turning demos into reliable systems.
