We build structured intelligence systems.
Revision Labs develops applied AI products powered by layered workflows, validation pipelines, and deterministic scaffolding.
Explore what we’re buildingApplied AI is powerful — but reliability requires structure.
Generation
Structured model orchestration with tool integration, controlled prompting, and modular inference pipelines.
Validation
Automated evaluation layers incorporating domain checks, signal scoring, constraints, and guardrails.
Structure
Deterministic output modeling using defined schemas, comparison frameworks, and inspectable reasoning.
Every product we build follows this layered architecture to reduce ambiguity and increase confidence.
Our brand name discovery platform.
BetterNamer applies structured AI workflows to brand name discovery — combining creative generation with domain availability, trademark screening, and search signal validation.
Generate
AI-assisted brandable name exploration.
Validate
Domain checks, trademark screening signals, SEO opportunity indicators.
Compare
Side-by-side scoring and structured evaluation.
Structured workflows for .NET environments.
ReviDotNet is our open-source framework for building structured AI workflows in .NET environments.
It separates inference, validation, and output modeling into composable layers — enabling systems that are flexible, inspectable, and reliable.
- Modular inference orchestration
- Signal-aware validation pipelines
- Deterministic output schemas
- Extensible tool integration
Builder mindset, enterprise experience.
Bryan Kruman combines enterprise sales leadership with hands-on technical execution. Over the past decade, he has led and expanded large-scale technology engagements representing tens of millions in annual value, working directly with executive stakeholders in regulated industries. His passion for engineering and commercial experience drive a disciplined approach to building reliable, intuitive systems that deliver measurable results.
LinkedIn GitHubCollaborate with us.
We're collaborating with investors, organizations seeking to apply structured AI in real-world environments, and developers contributing to our open-source framework.