NovaSense AI
Converses like a person. Extracts like a system.
Most sales chatbots either hold a decent conversation or capture structured data — rarely both. NovaSense runs two pipelines at once: one talks to your prospect, the other quietly reads the conversation and writes a complete, enriched record into your CRM before the session ends.
Web · Mobile · WhatsApp · Live chat · 17 languages
A prospect tells your chatbot their budget, their timeline, which competitor they're evaluating, and what would make them switch. Then the session ends, and all of it disappears into a transcript nobody reads. Manual CRM entry captures a third of the fields, on a good day.
Human-parity conversation
Persona adapts to how the prospect writes — formal or casual, technical or plain. It holds full session context, detects hesitation or frustration, and asks a targeted clarifying question rather than falling back to a canned reply.
Silent entity extraction
A parallel pipeline reads every turn for purchase intent, budget signals, stated requirements, competitor mentions, sentiment and geography — without adding latency to the reply the customer is waiting for.
CRM written in real time
Structured records land in Salesforce, HubSpot, Zoho, Pipedrive or Dynamics as the conversation happens. Custom webhooks push to anything REST-compatible.
Sales brief within 60 seconds
The assigned rep receives a readable summary — extracted entities, intent score, conversation highlights, and a recommended next action — before they open the CRM.
Running one frontier model for everything is slow and expensive. NovaSense routes each pipeline stage to the model that fits its actual demand — which is where most of the cost efficiency comes from.
| Pipeline stage | Model | Why this one |
|---|---|---|
| First-touch intent classification | Haiku 4.5 | Sub-100ms is non-negotiable here — any perceptible delay on the first reply loses the prospect |
| Turn-by-turn dialogue | Sonnet 5 | Best balance of naturalness, instruction-following and speed across a sustained conversation |
| Deep entity extraction and NER | Opus 5 | Catches implicit signals — an unstated budget ceiling, a soft objection — that lighter models miss |
| Post-session brief | Sonnet 5 | Structured synthesis, and it runs async so latency matters less than quality |
| Language detection and routing | Haiku 4.5 | Instant identification at minimal cost per token, on every single turn |
Figures from our own deployments. We'll walk you through the measurement method on a call — and share where the numbers are weakest.
We built it, we run it, we pay for every call it makes.
NovaSense is a production system our own engineering team designed, deployed and operates. That means we carry the uptime, the inference bill, and the consequences of our own architectural choices.
If you are evaluating an engineering partner, that distinction matters. Plenty of firms can show you work they shipped and handed over. Fewer can show you something they still own when it breaks at 3am.
Work with the team that built it →See it on your own sales conversations
Book a 30-minute call and we'll show you NovaSense running against a scenario from your business, not a scripted demo.