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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.