Your own model, not someone else’s service
A proprietary engine we train and evolve ourselves. You don’t depend on external cloud APIs, usage limits, or a third party’s terms of service.
NimbleGPT — AI that understands your meetings.
NimbleMeet’s own AI engine. At its core is speech recognition trained for the real acoustics of video conferencing: speakerphones, meeting rooms, SIP telephony, and mobile connections. On top of it — speaker separation, your names and terminology, and finished minutes with decisions and action items. Everything runs on your servers, with no data handed to a third-party cloud.
On-premise or APIMultilingualNo third-party cloudReal-time
Why a dedicated model
General-purpose recognition drifts on real meetings
Mass-market models are trained on clean studio speech and lose accuracy exactly where real conversations happen: on a speakerphone in a meeting room, over a phone line, on a mobile connection. The result is garbled names, mangled terminology, and unreliable minutes.
We trained NimbleGPT differently. The model is adapted to the actual acoustics of video meetings: telephony codecs, room reverberation, narrow-band audio, and noise. The result is accuracy that holds up where general-purpose solutions fall apart. Published benchmarks for the multilingual engine are on the way — ask us for early results on your own recordings.
Capabilities
What sets NimbleGPT apart
Six differences between an engine of your own and a generic cloud service.
Trained for real meetings
Adapted to the acoustics of actual video calls: speakerphones, conference rooms, SIP telephony, and mobile bridges — the conditions where general-purpose models lose accuracy.
Knows your names and terms
Upload a glossary of employees, products, and industry terms — the model starts recognizing them without retraining. Proper names stop turning into noise.
Live transcription
Text appears while the meeting is still running, with sub-second latency. Final accuracy matches offline processing.
Runs entirely on your servers
The whole pipeline works on-premise; data never leaves your perimeter. Fits isolated networks and strict information-security requirements.
From speech to outcomes
Not just a transcript: structured minutes — decisions, action items with owners and due dates, a summary, and search across your meeting archive.
Deployment options
AI that adapts to your hardware
The installer detects what your servers can do and picks the right mode — from fully air-gapped GPU inference to a managed API when no AI hardware is available.
01 Maximum isolation
AI on your server
Single-box deployment
A GPU node inside your perimeter runs the full NimbleGPT pipeline next to the conferencing platform. The only option for air-gapped and high-security environments.
02 Flexible hardware
AI on a second server
Split deployment
The conferencing server has no GPU? Run NimbleGPT on a separate GPU machine in the same network — the platform calls it over an internal API. Data still never leaves your infrastructure.
03 Zero GPU required
AI via cloud API
Consumption-based
No AI-capable hardware at all? Connect NimbleGPT as a managed API and pay per minute of audio. The installer detects your hardware and recommends the available mode automatically.
How it works
Three steps to finished minutes
Everything happens automatically, with no operator involved.
01
Hears the meeting as it is
NimbleGPT plugs into the conference and recognizes every participant’s speech — including phone and mobile connections.
02
Understands the context
Separates speakers, recognizes names and terms from your glossary, and produces an accurate transcript in real time.
03
Turns it into outcomes
Assembles structured minutes — decisions, action items with owners and due dates, key topics — and delivers them to email and your corporate systems.
Use cases
Who needs it
Government & regulated industries
Operates in an isolated perimeter with zero data sent to any cloud. Supports strict information-security and data-residency requirements.
Large enterprises
Minutes and action items are produced automatically after every meeting — no manual transcription, no lost follow-ups.
Distributed teams
Stable accuracy on phone and mobile connections, where general-purpose models tend to degrade.
Conference rooms & town halls
Tuned for speakerphones and SIP hardware — quality holds up even in acoustically difficult rooms.
Technology
For those who want the details
How the model is built and what it runs on.
- Model type
- Proprietary end-to-end neural speech recognition, multilingual
- Training
- Domain adaptation for meeting acoustics: telephony codecs, room reverberation, narrow-band audio, background noise
- Performance
- Many times faster than real time on a server GPU; multiple parallel streams per card
- Custom glossary
- Adapts to your names and terminology without retraining the model
- Deployment
- On-premise (including air-gap), split GPU node, or managed API
- Meeting minutes
- Automatic extraction of decisions, action items, and open questions
Demo
Let’s measure accuracy on your recordings
We’ll deploy a demo in your environment or show it on our test bench — and validate accuracy against your own recordings and terminology.