An AI-guided interview engine that turns busy technical staff into complete, audit-ready R&D tax evidence — in a conversation that takes minutes, not weeks of chasing.
Defensible R&D tax claims depend on detailed technical narratives that only engineers can provide — but engineers don't have time to write them, and tax teams can't extract them. The result is thin evidence, endless back-and-forth email chasing, and claims exposed to challenge from tax authorities.
AIRA runs a structured, adaptive chat interview with the person who actually did the work. It asks the right questions, probes for depth with intelligent follow-ups, and captures evidence mapped precisely to the qualifying criteria of each jurisdiction — automatically.
Admins define the interview in plain English — sections, question limits, pass thresholds and a country-specific compliance lens (e.g. HMRC R&D / AIF for the UK). AIRA converts it into live AI prompts at runtime.
The engineer receives a secure, OTP-verified link and answers a natural conversation. AIRA adapts on the fly, asks clarifying follow-ups, and lets them move freely between sections — no forms, no jargon.
Every answer is timestamped, threaded, and scored against qualifying criteria — feeding straight into the case file with a live completion and answer-quality metric for reviewers.
Each milestone anchors evidence to jurisdiction rules — but the respondent never sees framework names or tax terminology. They just answer questions about their work.
Intelligent follow-ups dig for the specific uncertainty and design reasoning that make a claim defensible — the depth a static questionnaire never reaches.
One engine, many compliance lenses. Configure the criteria per country; AIRA enforces them silently in every question.
No writing, no chasing. The person who did the work answers a chat once and the evidence is captured, scored and filed.
Timestamped threads, per-section coverage, and answer-quality scoring produce a traceable evidence record built to withstand scrutiny.
“When we tackled the inventory service, we used the dependency map to sequence its extraction after order intake but before billing… The contract tests caught two breaking changes before they hit production that would've otherwise caused silent failures.”
— Respondent answer to an AIRA follow-up probing reusable methods and measurable benefit. This is precisely the specific, technical, defensible detail that manual processes routinely fail to surface.