SigmaEra for Product
Customer truth reaches you third-hand, weeks late.
The most valuable product research your company runs happens every day in sales calls, support escalations, and success reviews — and then evaporates. SigmaEra turns those conversations into a queryable record of what customers actually said.
Customer truth reaches you third-hand, weeks late.
The arc a product leader walks with SigmaEra: where customer evidence actually lives, and what changes when you can query it instead of collecting anecdotes.
- 1The roadmap meeting
Everyone has a story and nobody has evidence
Sales says customers want one thing, support says another, and the loudest account gets weighted heaviest. You are arbitrating between anecdotes, each of them real and none of them representative.
What you have to answer
- How often has this actually come up, and with whom?
- Is this one loud account or a genuine pattern?
- What did the customer actually say, in their own words?
The layer that answers it
Conversation evidence
Sales calls, support escalations, and success reviews are canonicalized and made queryable, with themes and requests extracted and attributed to their source conversation rather than to whoever relayed them.
What changes for you
Prioritization arguments get settled with frequency and attribution instead of with confidence and volume.
- 2The lost deal
The objection nobody logged
A deal dies. The CRM says "price". The call recording says something quite different, but nobody had a field for it, so what reaches you is the closest available dropdown.
What you have to answer
- What actually happened in the conversations we lost?
- Which objections recur that our fields cannot express?
- Are we losing for the reason we think we are?
The layer that answers it
Extraction beyond the schema
Themes and objections are extracted from what was said rather than from what fitted a field, so the reasons that have no CRM dropdown are still visible and countable.
What changes for you
You stop optimizing against a taxonomy invented for reporting convenience and start seeing the real reasons.
- 3Discovery
Research you already paid for
You run a handful of research interviews a quarter. Meanwhile your company runs hundreds of customer conversations a week, conducted by people whose job is not research, into a record nobody reads.
What you have to answer
- What is in the conversations we are already having?
- Can I ask a question across all of them at once?
- How current is that evidence?
The layer that answers it
Ask across the corpus
A grounded question-answering surface over the accumulated corpus, returning answers assembled from the underlying conversations with links back to the evidence they came from.
What changes for you
Your largest research asset becomes usable, and it refreshes continuously instead of once a quarter.
- 4Post-launch
Did it land, and how would you know
The feature shipped. Usage metrics say people clicked it. Whether it solved the problem is a different question, and telemetry cannot answer it.
What you have to answer
- Are customers talking about this differently since launch?
- Did the objection it was meant to remove actually go away?
- What did it break that nobody filed a ticket about?
The layer that answers it
Longitudinal theme tracking
Because conversations accumulate over time, the frequency of a theme before and after a change is comparable — the qualitative half of the launch review, from evidence rather than impression.
What changes for you
You can answer whether it worked in the terms customers use, not only in the terms your analytics can count.
Control register
Every layer above is documented there in full, including the threat model and the control-status register.
Beneath the controls, the platform itself.
The five capabilities every SigmaEra deployment runs, read through the lens of this role.
Five stages · Protect → Emerge- 01
Protect
Customer conversations and roadmap material stay governed, with sensitivity classification applied before anything is indexed.
- 02
Orchestrate
One layer spanning sales calls, support escalations, and success reviews — the three places customer truth is spoken and then lost.
- 03
Automate
Recurring themes, objections, and feature requests are extracted and attributed, rather than depending on whoever happened to file a ticket.
- 04
Compound
Every conversation adds to a cross-meeting graph, so "how often has this actually come up" stops being a matter of opinion.
- 05
Emerge
Demand patterns surface that no survey was designed to ask about — including the objection nobody logged because it never fit a field.
The Compound Effect
Intelligence that builds on itself.
- 25%
- reduction in recurring meeting hours — with higher-quality outcomes in the meetings that remain.
- 10×
- faster strategic risk detection — surfaced from meeting and workflow data before it reaches the board.
- 1
- company-specific model — your corporate knowledge compounds into a private intelligence layer that gets smarter every week. Source: Platform security white paper — Model processing & training
Stop leaking data. Start compounding intelligence.
See How Product Teams Use SigmaEra
- Runs air-gapped inside your own boundary
- Full audit trail on every interaction
- 100 agents, one control plane