Your business runs on conversations. Almost none of it is captured.
MeetOS captures what is said in meetings — decisions, commitments, requirements, risks — attributes it to the person who said it, and turns it into structured business intelligence. It is the conversation layer of the AI-native business system Phenomeny is building.
Built for Indian enterprises · Hinglish-aware · Data stays in India
What it actually does
Not a note taker. A record of what your business decided.
Transcription and summaries are the starting point, not the product. The value is what happens after the words are captured: the commitment becomes trackable, the risk reaches the right person, and the decision is still findable in six months.
Captures the meetings you currently lose
Online calls, physical rooms and field visits. Most tools only cover the video call — which is where the smallest share of Indian business actually gets decided.
Understands how your teams actually speak
Conversations that switch between Hindi and English mid-sentence break English-only systems. MeetOS is built for that from the start.
Attributes every statement to a person
Not just a transcript. Each commitment is tied to who made it, with the audio to back it up — so "I never said that" stops being an argument.
Routes intelligence to whoever needs it
A risk raised in a review reaches the person accountable for it. A competitor mention reaches the account owner. Without anyone writing a summary email.
From conversation to structure
One sentence in a call. Five pieces of business data.
Raw conversation is unusable as business information. MeetOS reads it the way an analyst would — and writes it down the way a system can use.
What was said
[14:32] Rohit (Vendor): “Dekho, migration ka first phase we can close by the 30th, but the reporting module needs two more weeks. Aur pricing — if you commit to three years, I can hold it at the current rate.”
[14:33] Priya (CTO): “Two weeks is a problem. Board review is on the 5th.”
Today this lives in someone’s memory, a notebook, or a WhatsApp thread. By next quarter, nobody can prove what was agreed.
What MeetOS records
- CommitmentMigration phase 1 delivered by the 30th — owner: Rohit (Vendor).
- RiskReporting module slips 2 weeks; collides with board review on the 5th.
- Pricing discussionCurrent rate held in exchange for a 3-year term.
- Decision makerPriya (CTO) is the constraint-setter on timeline.
- Next stepResolve reporting timeline before the board review.
Each record carries the speaker, the timestamp and the audio it came from.
Signals extracted
Commitments
Who promised what, to whom, and by when.
Action items
The task, the owner and the deadline.
Decisions
What was actually resolved, and by whom.
Risks & objections
Concerns raised, pushback, blockers.
Opportunities
Buying signals and expansion openings.
Contradictions
The same person saying two different things.
Why this is built differently
A meeting assistant that stops at the summary is a dead end.
The problem was never that meetings lacked notes. It is that what your company knows stays trapped in the application it was created in. A standalone AI notetaker produces one more silo — a well-written one.
An isolated meeting tool
- Produces a summary someone still has to read and act on.
- Has no idea who in your company should see what.
- Cannot tell that a promise made today contradicts one made last month.
- Leaves your CRM dependent on people retyping what happened.
- Adds a database your team has to maintain by hand.
MeetOS as a layer in a system
- Every signal is attached to a person and a reporting line.
- Information is routed by role, not broadcast to everyone.
- Statements are compared across sessions, so contradictions surface.
- Designed so sales context can flow into SalesOS rather than be retyped.
- Operational data is a by-product of work already happening.
The progression
- 01
Conversation
A meeting happens — online, in a room, or in the field.
- 02
Intelligence
Speech becomes attributed, structured signals.
- 03
Organizational context
Signals are placed against people, roles and reporting lines.
- 04
Action
The right person is alerted, or the record is updated.
- 05
Business system
Operational data accumulates as a by-product of work.
The Phenomeny ecosystem
MeetOS is the first layer, not the whole system.
Each layer below has a distinct job. MeetOS captures what happens in conversations. The layers above and below it decide where that information belongs and what should be done with it.
Building · pilotsCaptures business conversations
Meetings, decisions, commitments and follow-ups become attributed, structured records instead of memory and scattered notes.
Controls organizational context and access
Determines how information should flow, who should have access to it, and where it belongs in the organization.
Available · integration on roadmapTurns customer intelligence into CRM context
Sales conversations become structured pipeline context, so the CRM stops depending on humans retyping what was discussed.
Extend the business context
Content Master, Workflow Automation and future modules progressively share the same context rather than operating alone.
Backend and data infrastructure layer
Intended to provide the underlying backend and data infrastructure the ecosystem runs on.
Long-term outcome · our vision
An AI-native business operating system
Where operational information is generated by the work people are already doing — rather than maintained by hand across disconnected tools.
How the systems work together
Two connections that change how a company runs.
MeetOS captures conversations today. The connections below are the direction of travel — described here as design intent, not as shipped features.
OrgOSRoadmapInformation that knows where it belongs
MeetOS can feed meeting intelligence into the organizational information layer. OrgOS is designed to decide how that information should flow, who should have access to it, and where it sits in the organization.
What that makes possible
- A risk raised in one department reaches the person accountable for it.
- Access follows role and participation — not a shared folder link.
- Leadership sees decision and commitment patterns across teams.
- Context stays with the organization when individuals move on.
Integration on roadmapA CRM that reflects what was actually said
Sales meeting intelligence can eventually flow into SalesOS, so the CRM stops depending entirely on people manually entering what was discussed. The pipeline becomes a record of real conversations.
Meeting intelligence as sales context
The goal is a CRM that gets more accurate the more your team talks to customers — instead of one that decays because nobody updated it.
The long-term direction
Where we believe business information is going.
Most companies run on systems that only know what someone remembered to type into them. Our view is that the next generation of business software will be fed by the work itself.
An AI-native ERP
Operational records generated from conversations and workflows rather than manual data entry across disconnected databases.
BharatBaaS underneath
Intended to provide the backend and data infrastructure layer this ecosystem eventually runs on.
Shared context, not silos
Products that pass context to each other, instead of each holding a partial copy of the truth.
To be clear about status: MeetOS is in active build with enterprise pilots. OrgOS, the SalesOS integration, BharatBaaS and the AI-native ERP described above are the long-term architecture — they are not deployed products today. We would rather tell you that now than after you have signed something.
Built for Indian enterprises
Recording conversations only works if people trust it.
A system that captures what people say has to be built consent-first and kept inside the country. That is a design constraint here, not a compliance checkbox added later.
Data stays in India
Hosted in AWS Mumbai (ap-south-1), with on-premise deployment available for stricter policies.
Consent is built in
The bot announces itself, physical recording plays an audible chime, and a consent log is attached to every session.
Your data is not training data
A contractual commitment that transcripts and recordings are never used to train models.
DPDP-aligned by design
Role-based access, configurable retention, and the right to delete an individual’s voice data on request.