Vision
AISAE provides shared audit templates, red-team evidence, and deployment attestations so smaller AI builders and adopters can demonstrate responsible practices without bespoke consulting. The vision is a practical assurance layer—fit-for-purpose, repeatable, and transparent—trusted by customers and regulators. Sponsors help level the playing field while improving safety outcomes across the ecosystem.
Problem
AI assurance is fragmented: frameworks differ, evidence is unstructured, and smaller teams lack expertise to assemble credible documentation. Procurement stalls because buyers can’t compare risk posture or find specific mitigations. As a result, beneficial deployments are delayed, and bad practices slip through due to process fatigue.
Solution
Cosolvent offers role-based workflows and evidence catalogs. With LLM+RAG, teams upload policies, test logs, eval reports, and incident playbooks and ask “which gaps remain for fine-tuned LLMs handling PII?” with citations to their own artifacts. ClientSynth simulates adoption timelines, audit outcomes, and customer concerns to help sponsors prioritize templates that unlock the most deals responsibly.
Business Model
Revenue arises from subscription tiers and certification facilitation; industry groups and public sponsors can underwrite domain specific packs (e.g., health, finance). Over time, anonymized, governed benchmarks on assurance maturity inform buyers and regulators, sustaining sponsor value.