Every sales call heard. Only the right ones need a human.

The problem

Most telecalling teams review calls the same way. Someone downloads recordings by hand, listens to a small sample, and passes feedback on days later. The rest of the calls are never heard.

That means:

• Managers guess. They see call counts, not what was said or why leads said no.
• Follow-ups slip. “Call me on Monday” lives in a caller’s memory or a notebook.
• Coaching comes late. By the time feedback arrives, the caller has made a hundred more calls the same way.
• Good leads hide. An interested prospect on call #87 of the day looks just like the 86 before it.

What CallSense does

Each recorded call goes through the same steps automatically, with no downloads and no manual sorting.

1. Recorded. Calls are picked up from your cloud telephony platform.
2. Prepared. Audio is cleaned up and split into the caller’s side and the customer’s side. Calls with almost no speech are set aside.
3. Transcribed. A speech model trained on Indian-accented, mixed-language speech writes down what each side said, with timestamps.
4. Analysed. A language model reads the conversation and fills in a structured call report.
5. Flagged. Simple rules choose the calls a person should check.
6. Reviewed. A reviewer confirms or corrects the report in a few clicks.
7. Reported. Dashboards and a daily digest turn every call into team-level numbers.

The call report

For every call with a conversation, you get:

Who it’s for

Any team that makes or takes a lot of phone calls in Hindi, Hinglish, Punjabi or English. It’s especially useful for these sectors across Himachal Pradesh, Punjab and the Chandigarh tricity:

Education and admissions

Universities, colleges, schools and coaching institutes calling students and parents during admission season. See who asked about fees, hostels or scholarships, who has already taken admission elsewhere, and which follow-ups are due before the deadline.

Tourism, hotels and travel

Hotels, homestays, resorts and tour operators handling enquiries for Shimla, Manali, Dharamshala, Kasauli and beyond. Spot booking-ready guests, track callbacks on quotes, and learn which objections (price, dates, room type) lose bookings in peak season.

Real estate

Developers and brokers in Chandigarh, Mohali, Zirakpur, Panchkula and the hill towns following up on ad and portal leads. Separate serious buyers from browsers, catch site-visit dates agreed on the call, and see which projects get the most interest.

Healthcare

Hospitals, clinics, diagnostic labs and IVF centres handling appointment and enquiry calls. Make sure every callback is made, and find out why callers don’t book. Strict privacy matters here, and CallSense can run entirely on the hospital’s own hardware.

Banking, insurance and loans

Insurance advisors, NBFCs, loan agents and bank sales teams calling customers for policies, renewals and loans. Track interest and follow-up dates on every call, and check that callers introduce themselves and explain products properly.

Built for every role on the team

For callers

• See your own calls, summaries and a coaching note on each one.
• Check the follow-ups you promised, so no callback is forgotten.
• Learn from feedback on today’s calls, not last month’s.

For team leads and managers

• Dashboard: a call funnel from recorded → conversation → interested or callback, outcomes per day, outcome mix per caller, caller-quality spread, top objections and lead temperature. Every chart links straight to the calls behind it.
• Daily digest: yesterday’s calls per caller, outcome breakdown, top objections, follow-ups due today and the number of calls flagged for review.
• Notes and tags: mark calls such as “good example” or “pricing” to build a coaching library.

For reviewers and QA

• A review queue, not a pile of recordings. Only flagged calls show up: hot leads, unhappy customers, low caller-quality scores, calls the AI wasn’t sure about, plus a small random sample to keep the AI honest.
• Click a line, hear the moment. The transcript is synced to the audio. Lines the AI used as evidence are highlighted.
• Confirm or correct in one step. If the report is right, one click confirms it. If not, change only the wrong field. Corrected values replace the AI’s everywhere: in totals, dashboards and the digest.
• Feedback that improves the system. Ratings and “what did the AI get wrong” notes are stored and used to tune it.

For business owners and admins

• Role-based access: callers see only their own calls; managers and reviewers see the whole team.
• Every transcript view and audio play is logged.
• System status at a glance: processing progress, failures and backups.
• Re-run any call with a different model or instruction set and compare the results side by side. Earlier results are always kept.

Why teams choose it

Every call, not a sample

Coverage goes from the handful of calls someone had time for to every recorded call. In our own deployment, about one call in four is flagged for a human. The rest are summarised, scored and counted without anyone needing to listen.

Built for how India actually talks

Calls switch between Hindi, English and Punjabi mid-sentence. CallSense uses a speech model fine-tuned on Indian-accented Hinglish and handles Hindi, Hinglish, Punjabi and English. Every report comes out in English.

Tuned to your campaign

Each campaign gets its own instructions: what counts as “interested” for a university admission call differs from a website sales call. A campaign word list fixes names and terms that speech models often mishear, such as your brand, product or course names.

Your data stays yours

Recordings and transcripts are never sent to cloud AI services. All transcription and analysis runs on private hardware, either ours or yours (see two ways to run it below). Access needs a login, is limited by role and is logged. Retention periods are configurable to support DPDP Act compliance, and the database is backed up nightly to separate storage.

Honest by design

• The AI never invents a follow-up date.
• It says when it isn’t sure, and those calls go to a human.
• It cites the transcript lines behind each verdict.
• Reviewer corrections always win, and every correction is kept for improving the system.

Gets better with use

Every review is a labelled example. We use them to measure accuracy on your own calls, compare AI models on real data and refine the instructions over time.

Fast

A typical call is transcribed and analysed in seconds. A full day’s calls are ready well before the next morning’s stand-up.

Two ways to run it

Both options use the same software, and in both your calls never touch a cloud AI service.

Results from our own team

We built CallSense for our own telecalling team first, and run it every day.

• 24,000+ calls and 250+ hours of audio processed since July 2026, across 20 caller extensions.
• About 1 in 4 calls flagged for human review. Reviewers no longer have to listen to everything.
• Fewer missed conversations. Better speech models and tighter definitions brought calls wrongly labelled “no conversation” down from 74% of analysed calls in our first test run to about 26% today.
• Real coaching data. Each caller now has an outcome mix, a quality score trend and a list of the objections they hear most.

Read the full story in what we learned analysing 24,000 sales calls.

Integrations

Available today

• Works with any cloud telephony platform: call recordings and call logs exported from it.
• Lead context from CSV (business name, category, notes).
• In-app dashboard and daily digest.

Coming next

• Real-time intake: calls processed automatically minutes after they end, pushed straight from your telephony platform.
• CRM write-back: summary, outcome and follow-up date added to the lead record.
• Daily digest by email or WhatsApp.

Using a CRM you’d like CallSense to update? Talk to us.