01 The claim graph
The claim graph
Paste messy investigation context and AVA generates a graph of claims, the evidence behind each one, and how they support or contradict each other.
Coherence engine
In development
A coherence engine for messy investigations.
AVA OS takes agent traces, incident notes, logs, eval failures, and hypotheses and pulls the mess into coherence: a structured belief model of claims, probabilities, constraints, and the next best question to ask. In plain language, it is a workspace for figuring out what probably happened when an AI agent or production system fails.
Paste the mess. Leave with a belief you can branch.
AVA OS converts ambiguous evidence into structured beliefs, testable claims, and next best investigation paths.
What it does
Turn scattered context into a belief you can inspect.
02 Belief projection
Belief projection
AVA projects a coherent belief state across the graph, so you can see what is probably true, what is still uncertain, and where the evidence is thin.
03 Branchable hypotheses
Branchable hypotheses
Branch an alternate explanation, change one assumption, and compare what moves. Investigations stay legible because every branch keeps its own reasoning.
04 The Oracle copilot
The Oracle copilot
Ask the Oracle what evidence to collect next. It reads the current belief state and points you at the question most likely to resolve the investigation.
Who it is for
Built for the teams stuck with ambiguous failures.
01
Paste the context
Drop in traces, incident notes, Slack threads, and eval failures. AVA OS does not need them clean.
02
Project a belief state
Generate the claim graph, see what coheres, and branch the explanations worth testing.
03
Ask what is next
The Oracle names the next best piece of evidence, so the investigation moves instead of stalling.
AVA OS