Understand your users better Without compromising their privacy
A local model on your infrastructure turns conversations into analytics. See what your users need, where they get stuck, and what your product is missing.
What people want appears in chat
Before it becomes a choice
That’s the clearest record of intent ever created. Yet most analytics miss it.
pgvector or Qdrant with per-tenant filters? → Compare · Vector search · Tenant filters
¿Por qué sube p99 al crear índices en Postgres? → Diagnose · Postgres · p99 / Index builds
Wie betreibe ich OTel in Kubernetes ohne Egress? → Deploy · OTel / Kubernetes · No egress
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Where users get stuck
Recurring friction and unmet requirements.
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Why competitors win
The trade-offs behind switching decisions.
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Where to expand next
Gaps your product could fill.
From conversations to insights
Privately, on your infrastructure
We install a local model on your infrastructure. It clusters conversations, classifies intent, and turns patterns into analytics for your team.
Global market insights
You couldn’t assemble alone
Combine your perspective with insights from other partners. Each gains access to a wider view none could assemble alone.
Data stays local
Global intelligence compounds
Some patterns only emerge across platforms. Observed Intelligence brings partner insights together, giving each partner access to context their own data can’t provide.
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See beyond your own data
Understand needs across products and markets through perspectives contributed by the network.
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Know where to focus next
See which needs recur across platforms to guide what you build, support, and invest in.
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Gain more with every partner
Each new contribution adds context. Every partner benefits from a richer shared view.