Insights & Research

Technical patterns, industry perspectives, and research from the team building deterministic decision authority for consequential execution.

Blog

Latest thinking

Governing RAG
Technical Pattern

Governing RAG with a Decision Plane

Why semantic similarity alone is not sufficient for production retrieval, and how a decision layer transforms RAG from a search problem into a decision problem.

Read more + Feb 12, 2026
Clinical AI
Industry Perspective

Why Clinical AI Needs Deterministic Decisions

In regulated healthcare environments, probabilistic outputs are not enough. How deterministic decision authority meets the bar for clinical decision support.

Read more + Feb 6, 2026
Agent Governance
Industry Perspective

Agent Governance vs Agent Evaluation

Evaluation scores model outputs after the fact. Governance enforces decisions before actions reach production. Why the distinction matters for enterprise AI.

Read more + Jan 29, 2026
Engineering

Why Agents Fail in Production

The gap between pilot success and production reliability is not intelligence. It is authority. A breakdown of the five most common production failure modes.

Read more + Jan 22, 2026
Technical Pattern

Deterministic vs Probabilistic Control

When should autonomous behavior be deterministic and when can it be probabilistic? A framework for deciding where the decision plane belongs in your architecture.

Read more + Jan 15, 2026
Product Update

Shadow Mode: Testing Rules Against Production Data

How shadow mode lets you validate new rules against real production traffic without executing them. See what would have happened before you turn anything on.

Read more + Jan 8, 2026

Case Studies

Governance in practice

Illustrative examples of how deterministic decision authority applies to real-world autonomous workflows.

Illustrative

Governed Multi-Step Workflows in Financial Services

Problem: A multi-step deal placement workflow produced inconsistent lender recommendations, with no way to trace why specific lenders were selected or excluded.

Approach: Memrail evaluated each step of the pipeline against business rules - filtering, weighting, fatigue management, and final recommendation - with decision traces at every checkpoint.

Results: Full decision reconstruction in seconds. Wrong decisions resolved before reaching production. Safe iteration via shadow mode before production deployment.

See the solution pattern
Illustrative

Safe Human-Facing Agents in Healthcare

Problem: A clinical decision support agent could not guarantee escalation for high-risk patient states, and effective intervention strategies were lost between sessions due to LLM drift.

Approach: Deterministic escalation pathways, intervention eligibility rules, and context directives ensured the agent always acted within clinical policy boundaries.

Results: Guaranteed escalation for every high-risk state. FDA-grade traceability for every decision. Shadow mode validation before clinical deployment.

See the solution pattern
Illustrative

Governed Retrieval for Knowledge Advisors

Problem: A knowledge advisory platform returned semantically similar content regardless of user context, source appropriateness, or whether the same sources had been surfaced repeatedly.

Approach: Pre-retrieval routing and post-retrieval filtering governed what content was appropriate to surface, with source fatigue management and persona-based eligibility rules.

Results: Content surfacing driven by policy, not just similarity. Explainable retrieval decisions. Source fatigue eliminated through cooldown rules.

See the solution pattern

Research

SOMA Architecture Preprint

Structured Orchestration with Memory and Authority - the architectural framework underlying Memrail. Request access to the full research preprint.

Request Research Preprint

See results in 14 days

The 14-Day Decision Authority Pilot: decision topology, domain analysis, controlled comparison, and an integration roadmap on your hardest workflow.

Let's talk