Answer Trace is a client-side product demo for evidence-first AI research. It turns a question into a visible workflow: scope the work, examine diverse evidence, extract claims, challenge weak reasoning, and publish only what the record can support.
Delivery model
Static client app
Data model
Curated fixtures
Product focus
Visible judgment
Customer problem
For consequential questions, people need more than a conclusion. They need to understand what was examined, what the evidence can support, where sources disagree, and when a system should stop short of a confident answer.
Product insight
Trust is not a confidence score alone. It is the ability to inspect the work that led to a recommendation.
Product solution
The demo replays a deterministic trace across three curated scenarios. A planner defines the work, researchers gather complementary evidence, a claim extractor builds the evidence map, a skeptical reviewer flags overreach, and a writer creates a concise decision brief.
Explore the workflowRequirements translated into product behavior
Make the question, scope, and decision boundary visible before generation begins.
Keep every recommendation connected to the evidence that supports or challenges it.
Treat disagreement and weak evidence as review signals, not output polish problems.
Give the reader a concise decision brief with limits stated plainly.
Engineering decisions
Makes every run instant, repeatable, inspectable, and safe to publish without secrets or user data.
Turns the agentic loop into a product interaction instead of a static architecture diagram.
Lets a visitor inspect the exact evidence and reviewer decision behind each statement.
Shows that a system can earn trust by declining to overstate incomplete or conflicting evidence.
What this demonstrates
Translated a trust problem into visible product requirements and interaction states.
Models planning, parallel research, extraction, review, and bounded synthesis as separate roles.
Delivers a responsive, keyboard-friendly experience built for fast exploration on desktop and mobile.
Makes uncertainty, escalation, and human judgment first-class product outcomes.
Deliberate boundary
This release does not include live web search, model calls, arbitrary user prompts, persistence, or a backend. Local fixtures keep the mechanics transparent. A future live mode would require a secure server-side integration, source governance, and product controls that are outside this small, public demonstration.