AI call analysis and conversation intelligence, inside your CRM
Upload a sales call recording. Insta AI 365 transcribes it, reads the conversation for intent, objections and commitments, and turns it into CRM work — the summary, the tasks, and the follow-up that was promised. You provide the recording; we do not record your calls.
Transcription · Conversation understanding · CRM actions
What Call Recording Intelligence does
Six things happen to a recording after you upload it. Every one of them exists in the product today.
Transcribes the recording
Speech-to-text with speaker separation, a detected language and a confidence score, stored as timed segments so any moment can be located in the call.
Reads the conversation
A single extraction pass produces a summary and key points rather than leaving you a wall of transcript to re-read.
Pulls out what matters
Customer intent, objections raised, commitments made, requests, buying signals, competitor mentions and overall sentiment.
Checks your red-flag phrases
Call Flagging AI matches the transcript against phrases your business configured, with a severity you set, and tells the people you nominated.
Writes the work into the CRM
Action items become open tasks on the deal, and the call with its transcript is attached to the record timeline.
Schedules or proposes the follow-up
A commitment with a clear time is scheduled. One that names a day but not a time, or that the transcript leaves ambiguous, is held for you to confirm.
How it works
Recording → transcript → understanding → extraction → flagging → CRM action.
- 01
You provide the recording
Upload the audio file, or connect it through the supported workflow. Insta AI 365 does not place or record calls.
- 02
Transcription
Speech-to-text with speaker separation, language detection and a confidence score. Segments carry timings.
- 03
Understanding
The transcript is read once, in context, rather than keyword-scanned.
- 04
Extraction
Summary, key points, intent, objections, commitments, requests, buying signals, competitor mentions and sentiment.
- 05
Flagging
Your configured phrases are matched against the transcript. A match records the employee, the moment and the surrounding context.
- 06
CRM action
Tasks written to the deal, the call attached to the timeline, and the follow-up scheduled or held for confirmation.
What it looks like
A representative interface. Nothing here is a customer record.
customer-call-aug-18.mp3
✓ Uploaded · transcribed · speaker-separated
Transcript
Sales rep: Would Thursday afternoon work for the site visit?
Customer: Yes, Thursday after 3 works. Please send the revised quotation before then — the current one is above what we budgeted.
Sales rep: Understood. I'll send the revised quote and call you Thursday afternoon.
- Summary
- Interested, progressing — wants a revised quote first
- Intent
- Purchase intent: high
- Buying signal
- Agreed to a site visit
- Objection
- Price above budget
- Commitment
- Site visit Thursday, after 3:00 PM
- Request
- Revised quotation before the visit
- Sentiment
- Positive
What happened in the CRM
- Call summary attached to the timelineOn the contact record, with the full transcript
- Task created — send revised quotationWritten to the deal as an open task
- Follow-up suggested — Thursday, 3:00 PMWaiting for someone to approve and schedule it
green = written automatically · amber = waiting for approval
Ira AI and call intelligence
They are the same AI layer applied to two different surfaces. Ira answers questions about the records in your workspace — which deals have gone quiet, what is overdue, what a contact's history looks like. Call intelligence points that same understanding at a conversation, and writes the result back onto the record Ira reads from.
That is the loop worth understanding: a call is analysed, its summary and tasks land on the deal, and the next time you ask Ira about that deal the conversation is part of what it answers from.
Call Flagging AI
Flagging is the part of the pipeline where your rules, rather than the model's judgement, decide what matters. You create a rule with the phrases you care about and set a severity — low, medium, high or critical. Each phrase is matched case-insensitively against the transcript, with word boundaries applied so a short phrase does not fire inside a longer word.
When a phrase matches, the flag records which employee's call it was, the phrase that matched, the moment in the call and the surrounding transcript context, and links it to the related lead, contact, company or deal. Notification recipients are configured per rule: a manager, a team lead, organisation admins, or specific people you name.
Flags are then worked, not just raised. Each one moves through open, acknowledged, resolved or dismissed, and carries who reviewed it and any note they left.
One distinction worth stating plainly: flagging matches the exact phrases you configured. Objections, buying signals, competitor mentions and sentiment are produced by the AI reading of the conversation, not by your phrase list. Both run over the same transcript, but one is your list and the other is the model's interpretation.
What happens in the CRM afterwards
Automatic: action items extracted from the conversation are written to the deal as open tasks, and the call — with its transcript and summary — is attached to the record timeline. Flag notifications are delivered to the recipients configured on the rule.
Scheduled for you: when the call ends on a commitment with an explicit time, or a window the system reads confidently, the follow-up is created without being asked. That is the point of listening to the call at all.
Held for you: a commitment that names a day but not a time is held for confirmation, and one the transcript leaves ambiguous is offered as a suggestion. The recommended next action is always a recommendation.
Never automatic: nothing is sent to your customer on your behalf. Call intelligence writes CRM records and proposes work; it does not message anyone.
What teams use it for
Nothing promised on a call gets lost
The revised quote, the callback time, the discount that was mentioned — extracted as commitments and written as tasks instead of living in someone's memory.
Managers see conversation quality
Flags carry the employee, the matched phrase and the transcript context, and move through open, acknowledged, resolved or dismissed as they are reviewed.
Handover without re-listening
Anyone picking up the account reads the summary and key points on the record rather than replaying a twelve-minute call.
Coaching from real calls
The extraction produces coaching tips and conversation quality metrics from the calls your team actually had.
Common questions
What is AI call analysis?
It is the process of converting a call recording into structured, usable information: a transcript, then a reading of that transcript for what the customer wanted, what they objected to, what was promised and what should happen next. In Insta AI 365 the output is written into the CRM as a summary, tasks and a proposed follow-up rather than left as a document to read.
Does Insta AI 365 record calls automatically?
No. There is no telephony, SIP or carrier integration in the product. You provide the recording by uploading the audio file or connecting it through the supported workflow, and analysis runs on that file.
How does call transcription work?
The uploaded audio is transcribed to text with speaker separation, so it is clear who said what. The transcript carries a detected language, a confidence score and timed segments, which is how a flagged phrase can be located at a specific moment in the call.
What happens after a recording is uploaded?
It is transcribed, then read once in context. That pass produces the summary, key points, intent, objections, commitments, requests, buying signals, competitor mentions and sentiment. Your configured red-flag phrases are checked against the same transcript. Tasks are then written to the deal, the call is attached to the record timeline, and the follow-up the call committed to is either scheduled or held for you to confirm, depending on how clearly it was stated.
Can Ira AI summarise calls?
Yes. The summary, key points and meeting notes come from the same AI layer that powers Ira elsewhere in the CRM, so a call summary sits alongside the records Ira can already answer questions about.
Can call intelligence create CRM actions?
Yes, and the boundary is worth stating precisely. Action items are written to the deal as open tasks automatically, and the call is attached to the timeline automatically. Follow-ups are graded: a commitment with an explicit time, or a clear window the system is confident about, is scheduled for you. A commitment that names a day but not a time is held for confirmation, and an ambiguous one is offered as a suggestion and nothing more. The recommended next action is always a recommendation. Nothing is sent to your customer on your behalf.
How does Call Flagging AI work?
You create a rule containing the phrases that matter to your business and choose a severity of low, medium, high or critical. Each phrase is matched case-insensitively against the transcript, with word boundaries so a short phrase does not fire inside a longer word. A match records the employee, the matched phrase, the moment in the call and the surrounding context, and notifies the recipients on the rule — a manager, a team lead, organisation admins, or specific people you name.
Is flagging the same as the AI analysis?
No, and it is worth being precise. Flagging matches the exact phrases you configured. Objections, buying signals, competitor mentions and sentiment come from the AI reading of the conversation. They run over the same transcript in the same pass, but one is your list and the other is the model's interpretation.
Explore the product
Ira AI
The assistant that answers from the records in your workspace.
AI-powered Automation
Workflows that assign, notify and schedule the next task.
Lead Management
Every enquiry in one list, with an owner and a next step.
Sales Pipeline
Deals, stages and what is actually going to close.
Pricing
Per user, per month, with published capacity limits.
See it on one of your own calls
Bring a real recording and judge it on whether the summary, the commitments and the follow-up match what actually happened.
Per user, per month · GST extra