Insights
Perspectives on AI, governance, and how Perspectis fits in the stack.
- Why We Build Tacit Knowledge Into Firm Context—Not Only TransactionsA plain-language Perspectis AI perspective: tacit knowledge as firm memory—structured “why,” targeted enrichment, connected journeys, and the Personal Agent Representative—without turning professionals into full-time data entry.
- Why We Built Perspectis AI Differently—and Why It Stays That WayA plain-language comparison of Perspectis AI with mainstream AI providers: enterprise governance, tenancy, human-in-the-loop, and professional workflows—not just chat.
- Why We Treat Agentic Intent as a Governance Contract, Not a MoodA plain-language Perspectis AI perspective: where agentic intent belongs in enterprise AI (policy, identity, tools, observability)—not only in prompts—and how we think about risk tiers and prompt injection.
- Why We Engineer AI Accuracy Without “Dynamic Exemplar” LibrariesA Perspectis AI perspective for leaders: accuracy as platform discipline—tenant-aware grounding, structured capabilities, and honest limits of similarity-Q&A retrieval—not hype about prompts alone.
- Why We Treat Human-in-the-Loop as Platform Design, Not a SloganA Perspectis AI plain-language perspective: human-in-the-loop as workflow-native approvals, compliance signals, assistant-action guardrails, and non-negotiable platform controls—not chat confirmations alone.
- Why We Treat Enterprise AI Policy as Platform Infrastructure—Not Prompt DecorationA Perspectis AI perspective for leaders: central governance policy, professional scoping (client, matter, business unit), honest versioning, auditability, and Model Context Protocol integration—without policy living in prompts alone.
- How We Think About Layered Information Security at Perspectis AIA plain-language Perspectis AI perspective on defence in depth: granular access, ethical walls, minimisation, monitoring, AI inside the same guardrails—and honest framing on certification versus product design.
- Why Data, Information, and AI Governance Are One Problem in Three LayersA plain-language Perspectis AI perspective: data, information, and AI governance as layered accountability, operational evidence, and the gaps we still treat as forward work.
- What Serious AI Accountability Actually Requires—and What Marketing Often SkipsA plain-language Perspectis AI perspective for leaders and risk owners: auditability as layered evidence across decisions, tools, security signals, and sensitive-data access—with honest limits on retention, immutability, and tamper-evidence claims.
- Three Questions That Separate AI Hype from AI AccountabilityA plain-language Perspectis AI perspective for leaders: reconstruction, explainability without crossing confidentiality walls, and what replay means in practice—including what we do not promise.