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Interpretable AI models and agents
At Guide labs, we build Interpretable foundation models and AI systems that can reliably explain their reasoning, and are easy to audit, steer and understand. We provide access to these models via our API.
Guide Labs builds interpretable AI systems and foundation models designed to be reliably debugged, trusted, and understood by humans. They emphasize an auditable, transparent approach to AI with a product focus called Access Clarity and a background in interpretable ML research.
The company develops interpretable AI systems and foundation models, including an inherently interpretable platform named Access Clarity. Their work includes research on prompt attribution to identify which parts of prompts drive outputs, and they have developed interpretable diffusion models and LLMs. The product aims to make AI outputs auditable and understandable so humans can debug and trust the results.
Who it’s for: Organizations and teams needing auditable and interpretable AI, including research-driven enterprises, AI safety/compliance-focused buyers, and developers seeking transparent model behavior.
Hiring/traction mentions not explicit; references to research papers and investors imply early-stage R&D with potential funding involvement.
I am a machine learning researcher working on interpretable AI systems.
Foundation models that can explain their reasoning, and are easy to align
Guide Labs builds interpretable foundation models that explain their reasoning and are easy to align. They provide human-understandable explanations, indicate important parts of the prompt, and show which tokens influenced outputs, enabling debugging and alignment to fix errors.
From the original launch (Mar 2024) — may be outdated.
AI system design tools for dev teams
The deterministic layer for frontier intelligence
