Sales enablement · Artificial Intelligence
Sales AI — real-time call intelligence
Real-time intelligence that listens to live sales calls, transcribes both sides, reads sentiment and buyer interest, and delivers in-the-moment coaching — with live quality control and performance-based lead routing for managers.
Project
Global scale · edge speech with a central hub
Phased, de-risked delivery
Discuss a similar brief
The challenge
Where things stood.
Real-time intelligence on live human conversation is one of the hardest problems in applied AI. A coaching platform has to transcribe speech as it is spoken — across accents, background noise and phone-quality audio from anywhere in the world — and understand it well enough to coach a live person, all within a couple of seconds.
It must do this affordably at the scale of thousands of concurrent calls, and handle sensitive conversation data responsibly. Accuracy, latency, cost and privacy had to be met together, not one at the expense of the others.
How we built it
Delivered in deliberate phases.
- 01
A validated speech foundation
A streaming recognition pipeline was built and proven end to end behind a single, stable interface, so any speech engine — self-hosted or cloud, streaming or batch — can be swapped in without changing anything downstream. Build-versus-buy never became a one-way door.
- 02
A two-speed architecture
A fast, low-latency speech layer runs close to the call and produces the live transcript instantly, while a separate intelligence layer applies deeper understanding only on the moments that matter. The language model is kept off the real-time critical path entirely.
- 03
Intelligence that measures meaning
Sentiment is read as conversational intent rather than surface politeness; the interest score is weighted toward genuine signals and validated against real outcomes; and compliance is judged by whether key points were covered in meaning, not by literal word-matching that would punish skilled paraphrasing.
- 04
Coaching, compliance and routing
Instant corrective guidance, pitch and objection handling, live listening for managers and semantic compliance feed a routing layer that directs premium leads and support to where they help most — with people reviewing the consequential decisions.
- 05
Omnichannel and scale
Channel adapters normalise phone, browser and video-meeting calls into one internal format, and a hub-and-spoke deployment lets each location run its own real-time processing while a central hub coordinates models and analytics.
What we delivered
The work.
- A real-time streaming speech pipeline behind a swappable engine interface
- A two-speed design that keeps live transcription instant and runs heavy AI only when triggered
- Live sentiment, a validated buyer-interest score and semantic compliance measured against real outcomes
- Real-time pitch suggestions, objection handling and corrective guidance drawn from the team's playbook
- Manager live-listening, quality control and performance-based lead routing
- Edge-plus-hub deployment so sensitive call audio can stay within an organisation's own environment
Outcome
What changed.
- Every live call becomes a coaching opportunity, helping each representative perform like the team's best
- Managers gain real-time visibility, consistent compliance and a data-driven way to route leads
- Representatives get in-the-moment support to handle objections and read the room
- Cost scales with meaningful moments rather than raw minutes of audio
- Sensitive conversation audio can remain on-site or at the edge, with only necessary intelligence handled centrally
Accuracy, latency, cost and privacy are usually traded against each other. Fast speech at the edge, with heavy AI only when it earns its place, is what lets a product have all four at once.
Customer support
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One grounded AI at the centre of every support channel — web chat, email, messaging and live phone calls — resolving routine enquiries around the clock and escalating to a person only when it should.
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