For enterprise implementation teams
Requirements gathering at the scale of the whole organisation.
Every large software implementation depends on understanding how thousands of people actually work, across functions, regions, and languages. Tadeus runs that discovery as real voice conversations, in parallel, and returns structured requirements instead of a backlog of workshop notes.
No audio kept · No video · No emotion inferred from voice
Why discovery stops being the bottleneck
Days
To run organisation-wide discovery, not months of workshops
Every
Function, region, and language reached in one pass
Structured
Requirements out, not raw transcripts to synthesise
The discovery bottleneck
Implementations don't fail on code. They fail on understanding.
The riskiest phase of any enterprise rollout is finding out how work really happens before you change it. Workshops and interviews don't scale, and the gaps they miss become change requests, rework, and abandoned modules later.
Workshops reach a fraction
A handful of stakeholders speak for thousands of users whose real workflows never get captured.
Edge cases surface too late
The exception that breaks the configuration shows up in UAT, not in discovery.
Language limits the sample
Non-English sites get under-consulted, so the design is biased toward headquarters.
Notes aren't requirements
Synthesising dozens of sessions into a clean spec is slow, lossy, and inconsistent.
No baseline to measure against
Without structured 'before' data, you can't prove the new system actually improved anything.
Consultant time is the cost
Discovery at scale means more billable interviewers, not better coverage.
How it works
Discovery that runs in parallel.
Tadeus turns requirements gathering from a sequence of meetings into a single deployable conversation that everyone can complete in their own language.
- 01
Design the discovery conversation
Define what you need to learn: current workflows, pain points, exceptions, must-haves. Set it once, for every team and region.
- 02
Deploy across the whole user base
Every affected employee completes a structured voice conversation, natively in their language, without scheduling.
- 03
The agent probes and clarifies
It follows up on vague answers, captures concrete examples, and branches into the workflows that matter for each role.
- 04
Get structured requirements back
Themes, frequencies, exceptions, and priorities come back as structured data ready for the design and config team.
- 05
Validate the build, then prove the lift
Re-run after go-live to confirm fit and quantify the improvement against your discovery baseline.
What the implementation team gets
Complete coverage, clean requirements.
Discovery that finally matches the scale of the systems you're implementing, without adding a small army of interviewers.
Reach every user, not a sample
Hear from the whole organisation so the design reflects how work actually happens everywhere.
Every language, no bias
Native multilingual conversations remove the headquarters bias from global rollouts.
Requirements, not transcripts
Structured themes, exceptions, and priorities come out ready for configuration.
Catch exceptions early
Surface the edge cases in discovery instead of paying for them in UAT and rework.
A measurable baseline
Capture the 'before' state so you can prove the implementation delivered real change.
Enterprise-safe by design
Voice only, no audio retained, no emotion inference, clear of the EU AI Act line.
Built for the phase that decides the project.
Directional impact of moving discovery from sequential workshops to a parallel voice layer.
Days
To complete organisation-wide discovery
100%
Of affected users reachable, not a stakeholder sample
70+
Languages handled natively in one design
1
Conversation design, deployed everywhere at once
Built for regulated workplaces
Compliant by design, not by disclaimer.
The EU AI Act prohibits emotion inference in the workplace from February 2025. Tadeus was built clear of that line from day one, so the hardest question an enterprise buyer asks is already answered.
No audio retained
We work from the transcript. Raw audio is never stored.
No video or faces
Voice only. No facial biometrics, nothing the camera captures.
Comprehension, not emotion
We read what was said, not feelings inferred from how it sounded.
Configurable by region
Region-gated controls so EU deployments stay clear of the AI Act line.
GDPR-aligned · We do not train models on your data · Data encrypted in transit and at rest
FAQ
Questions teams ask us first.
How does Tadeus gather requirements at scale?
It runs structured voice interviews with every affected user in parallel, probes for concrete examples and exceptions, and returns themes, frequencies, and priorities as structured requirements, not a backlog of workshop notes to synthesise.
How is this better than stakeholder workshops?
Workshops reach a handful of people who speak for thousands. Tadeus reaches the whole organisation in days, so edge cases surface in discovery instead of UAT and the design reflects how work actually happens everywhere.
Does it work across regions and languages?
Yes. 70+ languages natively, so non-headquarters sites are consulted on equal footing and you get one comparable dataset instead of a HQ-biased sample.
Is the data enterprise-safe?
Voice only, no audio retained, and no emotion inferred from voice, clear of the EU AI Act line.
Make discovery the strength of your next implementation.
See how Tadeus gathers requirements across your whole organisation in days, and gives you a baseline to prove the rollout worked.
Or talk to us about a large rollout