About Builds Experience Writing Contact
Home/ Builds/ Prospect Call Intelligence Agent
AI Agent · Built-in Analysis Skill

Prospect Call Intelligence Agent

Most call tools tell you what was said. This agent tells you why it matters — surfacing buyer intent signals, product and enablement gaps, and competitive pressure that feed a continuous improvement loop for sales and marketing teams.

See the output
Vikraya — Prospect Call Intelligence Agent
Vikraya
Prospect Call Intelligence Agent
100+ Calls decoded
12 KPIs Per workbook
5 types Signal coding
2 gaps Product vs Enablement
The gap

Why existing call tools aren't enough

What every other tool gives you

A smarter meeting recorder

AI note-takers across the board — they transcribe, summarise, and generate action items. They answer "what was discussed?" efficiently. But none of them can tell you whether the prospect is likely to walk away, whether a gap is a product limitation or a rep training issue, or how your positioning is landing versus the competition. They close no improvement loop. They're note-takers, not analysts.

→
What this agent does instead

Intent decoding and gap intelligence

Every signal in every call is coded — not paraphrased. Asks, Objections, Non-negotiables, AI stance, Proof-requests, competitive mentions. Product gaps are separated from enablement gaps so you know what to build versus what to train. Priority signals are ranked. The output feeds directly back into your sales motion, product messaging, and battle-card updates — a continuous loop, not a one-time note.

Other call tools

Note-taking mode

  • Meeting summary and transcript
  • Action items and follow-ups
  • Speaker attribution (who said what)
  • Keyword search across recordings
  • CRM sync for notes and tasks
VS
This agent

Intelligence mode

  • Buyer intent coded by signal type and priority
  • Product gaps vs. enablement gaps separated
  • Non-negotiables distinguished from objections
  • Competitive mentions and AI stance tracked
  • Positioning themes mapped to prospect language
  • Continuous PMM + sales improvement loop

No current tool does this. Every AI note-taker on the market operates in summary mode. This agent operates in signal-coding mode — every discrete statement from the prospect is classified, ranked by priority, and routed into a workbook your PMM, sales, and product teams can act on immediately.

Demo

One command. One workbook.

The agent ships with a built-in analysis skill. Trigger it, paste the transcript — Teams, Zoom, Meet, or any read.ai export — and the agent runs the full pipeline with no configuration, no back-and-forth, no interpretation layer.

Triggering the prospect call intelligence agent — built-in skill invocation
Process

How it works

Two stages. The LLM codes intent; Python renders intelligence. Neither stage substitutes for the other.

01
🎙

Transcript in

Paste or upload from any platform. Any format, filler words and all. Zero pre-processing required.

02
📖

Intent coded

Every signal mapped to a controlled vocabulary. No paraphrasing — verbatim quotes only, coded by type and ranked by priority.

03
📊

Two CSVs written

call_data (33 cols, 1 row) and signal_data (18 cols, one row per discrete Ask / Objection / Non-negotiable / AI-signal / Proof-request).

04
⚙️

Python renders

build_call_analysis.py runs deterministically. Same CSVs always produce the same workbook. The LLM never touches the spreadsheet.

05
📋

Intelligence delivered

Five-tab .xlsx — Dashboard, Drilldowns, Calc, Signal_Data, Call_Data — with 12 KPI tiles, 8 charts, and hyperlinked drilldowns to every signal row.

Output

What the intelligence brief looks like

Every workbook contains the same structure — 12 KPI tiles, 8 charts, and a full drilldown to the underlying signal row. Not a summary. A coded record.

Dashboard tab — 12 KPI tiles and 8 charts
Dashboard tab — 12 KPI tiles (Signals, Asks, Objections, Non-negotiables, AI-signals, Proof-requests, Product gaps, Roadmap/Beta, Enablement gaps, Dealbreakers, Stated-High, Cannot-fully-meet) + 8 charts showing signal distribution, gap type split, sentiment, and deal stage
Signal_Data tab — coded signals with verbatim quotes
Signal_Data tab — every coded signal with Demand Object Class, Verbatim Quote, Speaker role, Priority, and Sentiment. Filterable. Not paraphrased.
Codebook vocabulary — controlled values for all fields
Controlled vocabulary — 15+ fields with fixed allowed values: vertical, region, deal stage, capability area, signal type, and more. The same codebook on every call.
Decision rules — tie-break logic for ambiguous coding
Decision rules — 13 tie-break rules that eliminate subjective coding: Gap_Type (product vs. enablement), Non-negotiable vs. Objection, capability area disambiguation. No two analysts code the same call differently.
Why it matters

The loop it closes

Directional outcomes from production use across PMM and sales teams.

100+ Calls decoded

Not summarised. Every signal coded, ranked, and routed into the workbook — from a senior buyer's non-negotiable to a technical evaluator's proof-request.

2 gap types Separated, not merged

Product gap vs. Enablement gap. Every unmet need is classified so product and sales leadership know exactly who owns the fix — no more ambiguity about whether to build or to train.

Zero Note-taking mode

No summaries, no action items, no meeting minutes. Every output is a structured intelligence brief that feeds directly back to PMM messaging, sales enablement, and product roadmap decisions.

Interested?

Ask me to walk you through it

I can run a live demo on a real transcript. If you're thinking about a similar signal-intelligence layer for your sales or marketing team, let's talk.

Get in touch Back to all builds