Capture.
Capture a meeting, call, or existing source without losing the oral context.
French software · built by Hyle Labs
Your meetings, structured as decisions and actions to review.
After a meeting, the essentials get lost: who decided what, by when, in which tool. Taveni is designed to structure decisions and actions for your teams to review before any external handoff. The path to a business tool is verified and scoped during the evaluation.
Decisions linked to their evidence · Actions with who, what, by when · Human validation before sending
Goal: less unnecessary context. The evaluation measures what structured context avoids reprocessing without claiming savings before observation.
Your corrections stay under your control. Their storage, use, and any sharing with third-party models or tools are scoped before the evaluation.
The problem
Your best decisions are made out loud. Then they vanish.
Summary tools produce recaps that nobody reopens. The real value is elsewhere: in the decisions your teams make out loud, own, and need to find, review, and execute.
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The decision evaporates.
Budget, priority, an exception granted to a customer: the decision is made out loud, then lost inside a long transcript.
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The next step is too vague.
"I'll handle it" is not clear enough to create a reliable task in a project or support tool.
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Nothing reaches the tools.
The recap exists, but the action reaches neither the CRM, support desk, nor project tool — and nobody controls who can see what.
Two angles often forgotten: access rights and the AI bill
- Sensitive information — sharing everything with an assistant or integration is not acceptable for every account, project, or topic: access rights must follow the decision.
- The AI bill — the cheaper AI gets, the more everything is sent without filtering; you end up paying a lot for noise.
Taveni is designed to turn meeting material into sourced operational memory: decisions and actions to review before any handoff. The evaluation verifies what is actually retained, useful, and reusable in your workflow.
Workflow to evaluate
Capture › Qualify › Review › Prepare the handoff.
The evaluation verifies what can be captured, structured, and reviewed. A handoff to a business tool is included only after human approval and verification of the destination path.
Qualify.
Add roles, projects, vocabulary, access rules, evidence, and expected destination.
Review.
Confirm important decisions and actions or keep incomplete items pending.
Prepare the handoff.
After approval, use the connector verified in scope or a documented manual export.
See how it works in detail
- Capture — the meeting audio (or an existing file) is transcribed and timestamped, to link every passage to the exact moment it was said.
- Qualification — Taveni proposes decisions, actions, and risks with an owner, deadline, access rule, and destination to verify.
- Review — your teams confirm, complete, or reject; this review never grants implicit permission to write elsewhere.
- Handoff — after explicit approval, the result follows the path verified during the evaluation: an included connector or documented manual export.
Where to start
TeamTypical meetingWhat Taveni does with it
LeadershipCommittees and trade-offsFind why a priority, budget, or date was approved, with the excerpt and expected next steps.
Sales & CSCustomer meetingsCommercial commitments become proposed actions to review; the CRM, support, or follow-up handoff is selected and verified during the evaluation.
Product & opsOperational decisionsWhat was decided across teams stays visible, including actions without a clear owner.
Positioning
Taveni starts where automatic notes stop.
Automatic notes tell you what was said. Taveni aims to structure what deserves operational review: source, owner, status, access rule, and proposed destination. The evaluation verifies this behavior on a bounded workflow.
Why sending everything to AI gets expensive.
As AI gets cheaper, more unfiltered context may be sent back through it. Taveni is designed to separate raw verbatim from qualified information. The context avoided and its cost effect must be measured during the evaluation, not promised in advance.
The Jevons paradox, in a nutshell
When a resource gets cheaper, its use may increase. For AI, that makes calls and processed context worth measuring; the Taveni evaluation compares the baseline with the observed scope without assuming the outcome.
TopicClassic AI notes toolTaveni angle
SummaryProduces a readable summary, often detached from execution.Isolates the decisions, actions, risks, and evidence worth keeping.
QualificationDetects tasks or next steps from the conversation.Requires source, owner, right, review status, and destination.
ExecutionSends notes or actions based on available integrations.Prepares a handoff after validation; the actual path is verified during the evaluation.
ControlControls vary by product and configuration.Requires access, destination, retention, and cost to be scoped before the handoff.
The cost of AI
Measure the context that is actually useful before reprocessing it.
Cost depends on the model, volume, and workflow. The evaluation compares a baseline with the context actually processed without promising savings before measurement.
How context gets qualified
When an A2A/MCP context flow is included and verified, meeting profile, business vocabulary, and organizational context are qualified before extraction. Source, owner, access, and destination rules are tested in scope; they do not prove general availability.
{
"meeting_title": "Q3 sales review",
"participants": [
{ "name": "Nathalie Dupont",
"role": "CFO" },
{ "name": "Karim Benali",
"role": "Sales Lead" }
],
"user_profile": {
"company": "Hyle Labs",
"job_title": "Finance lead"
},
"vocabulary": [
"ARR", "renewal", "Q3 committee"
],
"org_projects": ["Q3 Expansion"],
"org_clients": ["Acme Corp"],
"org_products": ["Taveni"],
"output_instruction": "Prioritize decisions, actions, and evidence.",
"routing_rules": "Do not send without owner, source, or right"
}whodirectory and roles clarified
whatprojects, clients, vocabulary retained
measureprocessed context compared with baseline
Trust & sovereignty
Delegate the task, not the learning.
An AI proposal has operational value only after human review. The evaluation documents how decisions, corrections, and rules are stored, protected, and reused; it assumes no absolute portability or protection.
Detected phraseQuestion to resolveNext step
"We approve the Q3 budget"Can we find the excerpt that supports this decision?to verify
"I'll handle it Monday"Are the owner, deadline, and subject clear enough?to complete
"Confidential account topic"Should this information remain limited to certain people?to confirm
If the model changes, the evaluation verifies which decisions, corrections, and rules remain exportable and reusable within the agreed scope.
InformationOriginState
decisionmeeting · 00:17:42 · oral proofvalidated
commitmentspeaker · excerpt · confidenceneeds review
riskaccess rules · confidentialityrestricted
- Sourced decisions. The evaluation checks the link between a decision and its evidence before sharing or handoff.
- Share the minimum useful context. The scope states which information each tool or assistant may receive.
- Sensitive data. Access, services used, retention, and sending rules are documented before the evaluation.
- Learning loop. The evaluation measures whether validations, rejections, and corrections improve later suggestions.
Measure value, not hype.
A Taveni evaluation does not promise full automation. On one of your real processes, it measures four simple things:
search time · manual re-entry · qualified incidents · observed AI cost
Hyle Labs
AI products that turn speech into capital.
We build products for teams whose decisions and actions move between conversations, tools, and assistants. Taveni is designed to structure oral decisions as decisions, evidence, and actions to review within a verified scope.
Our guiding line is simple: delegate the task, not the learning. AI should reduce manual entry without taking away the team's ability to review, limit, and decide what gets executed.
“I created Taveni because our teams' most important decisions lived in recaps nobody reread. We're building the tool that makes them executable — without ever taking the decision away from humans.”
Adryan Perez — founder, Hyle Labs · Lyon
French SASU · RCS Lyon · Taveni in scoped evaluation
Talk with us
Measure Taveni on a real workflow?
Send us your context: meeting type, target tool, GDPR constraints, and success criteria. We'll reply with a proposed scope, measurement criteria, and the conditions required for the evaluation.
Straight answers
Do we need to change tools to use Taveni?
Not necessarily. The evaluation starts from your current toolset and defines one handoff. Depending on verified availability, that handoff uses an in-scope connector or a documented manual export.
Where does the data go? (GDPR)
Processing depends on the agreed scope. Before an evaluation, we document the data involved, services used, access, retention, and deployment constraints.
What happens if we switch AI models?
The evaluation documents what remains stored, exportable, and reusable if the model changes. Portability depends on the verified product scope, formats, and contract terms.
How much does it cost?
Taveni is in a scoped evaluation phase. Scope, success criteria, required resources, and commercial terms are defined before anything starts.
Which tools do you connect?
Evaluations target one handoff to a CRM, support, or project-management tool. Connector availability is checked during scoping; a manual export may be used as a fallback.