CallIntell — AI Call Synopsis & Quality
Every call summarised into the CRM, without anyone listening
Built by Esparks IT Solutions · architecture & delivery led by Faiz Akram
CallIntell turns recorded phone calls into reviewed, structured records in the CRM, without anyone listening to the call. A recording lands, it is transcribed with speaker labels, personal data is stripped before it reaches a language model, the call is matched to its CRM record, and a synopsis — outcome, commitments, follow-up date — is written back as a note and a scheduled task. Anything the system is unsure about goes to a human queue instead of being guessed.
CallIntell turns recorded phone calls into reviewed, structured CRM records without anyone listening to the call. A six-stage queue-backed pipeline fetches the recording, transcribes it with speaker labels and word-level timestamps on serverless GPU, strips personal identifiers before any text reaches a language model, matches the call to its CRM record, and generates a schema-validated synopsis — outcome, commitments, objections, price discussed — with every point linked to the second of audio it came from. Spoken follow-up phrases are resolved into dated tasks in the customer's own time zone. Anything the system is not confident about routes to a human review queue rather than being guessed, and CRM writes are idempotent so a retry cannot duplicate a note or a task. Built on Next.js, BullMQ, PostgreSQL, WhisperX with diarization, Presidio redaction and Claude, with passkey sign-in, an append-only audit log and per-company isolation.
The Problem
Somebody has to listen to every call. That does not scale, and it is the first thing cut.
A team listens to calls and types up what happened
On a floor of any size, summarising calls is a full-time job for a group of people. They listen at double speed, skim, and still cannot cover everything — so coverage quietly becomes a sample rather than the whole.
The CRM record is written from memory, hours later
By the time a summary is typed, the detail has gone. What the customer actually committed to, the price that was quoted, the exact words they used about calling back — the specifics that matter are the first to be lost.
"Call me in a couple of weeks" never becomes a task
Follow-up dates live in the recording and in somebody's head. Unless a human converts the phrase into a dated task on the right record, the callback does not happen and nobody notices.
Recordings contain data that must not reach a model
Customers read out card numbers, bank details and government identifiers on the phone. Sending raw transcripts to a language model is the easy way to build this, and the wrong one.
CallIntell does the listening. People check the few results the system is not sure about, and the rest is written to the CRM unattended.
How It Works
- 1.The call ends
- 2.The recording is stored
- 3.It is transcribed and redacted
- 4.It is matched to a CRM record
- 5.A synopsis is generated
- 6.The follow-up date is resolved
- 7.Confidence decides the route
- 8.The CRM is updated
Key Highlights
- Six-stage retryable pipeline: ingest, transcribe, match, synopsise, review, CRM write-back
- PII redacted in the transcription worker, before any text reaches a language model
- Spoken follow-ups resolved to dated CRM tasks in the customer timezone
- Low-confidence results queue for a human instead of being guessed