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Why Verist ​

Verist is a deterministic, audit-first workflow kernel for AI systems. It gives you replay, recompute, and diffs for AI decisions – so you can upgrade models and prompts without guessing what will break.

The trust gap ​

Modern AI workflows create failures you cannot reproduce:

  • Decisions change silently with model or prompt updates
  • Logs show what happened, but not why
  • Human corrections get overwritten by recomputation
  • Agent frameworks introduce hidden state and emergent control flow

Acceptable for demos. Not for review-heavy or high-impact systems.

What Verist gives you ​

CapabilityDescription
Replay + diffCapture artifacts during a run, replay exactly, or recompute and review the diff before shipping
Database-backed stateAll state lives in your database. Steps return outputs; nothing important is implicit or in memory
Audit-firstEvery step produces structured audit events. The evidence trail is part of the API, not optional logging
Human authorityHuman overrides are first-class and survive recomputation
Minimal kernelSmall, explicit library that fits under your existing runner, queue, and UI

How Verist differs from agent frameworks ​

Agent frameworks optimize for autonomy and speed. Verist optimizes for control and accountability.

DimensionAgent frameworksVerist
Primary goalAutonomy, speedTrust, correctness
Control flowOften implicitExplicit, code-defined
StateIn-memory + checkpointsDatabase as source of truth
ReplayBest-effortExact, artifact-based
AuditabilityOptionalCore primitive
Human overridesFragilePreserved by design

Verist can sit underneath an agent framework when you need guarantees, or replace ad-hoc scripts when a workflow becomes critical.

When Verist fits ​

Use Verist when:

  • AI decisions must be reproducible and explainable
  • Model/prompt upgrades need reviewable diffs
  • Human review is part of the workflow
  • You are accountable to audits, compliance, or users

When to skip Verist ​

  • Internal chatbots without audit or replay requirements
  • Fast prototypes and throwaway scripts
  • Exploratory agents where outcomes are intentionally non-deterministic
  • One-off scripts where you don't need diff or long-term replay

If you want speed over correctness, Verist will feel heavy.

LLM context: llms.txt · llms-full.txt
Released under the Apache 2.0 License.