Call Summary

Execution Steps

Step 1: Ingest Call Content

Accept one of the following inputs:

• Raw transcript (pasted text or file path)
• Unstructured call notes (bullet points, shorthand)
• Audio transcript file (if pre-transcribed)

If the input is extremely brief or unclear, ask clarifying questions:

• Who was on the call? (names, titles, company)
• What stage is this deal in? (first call, follow-up, negotiation)
• What was the primary purpose of the call?

Step 2: Extract Key Information

Parse the call content and extract these categories:

Attendees & Context:

• All participants (name, title, company)
• Call date and duration (if available)
• Deal stage at time of call

Pain Points Identified:

• Explicit pain points stated by the prospect
• Implicit pain signals (complaints, workarounds, frustrations mentioned)
• Rank by severity: Critical / High / Medium / Low

Objections Raised:

• Pricing objections — note exact concerns (too expensive, unclear ROI, budget constraints)
• Timing objections — not now, next quarter, need internal buy-in
• Technical objections — integration concerns, data security, team readiness
• Competitive objections — already evaluating alternatives, incumbent solution

Budget Signals:

• Any budget mentioned (explicit numbers or ranges)
• Budget authority indicators (who decides, approval process)
• Procurement process clues (vendor registration, PO requirements)

Decision-Making Signals:

• Decision maker identified? (name, title)
• Decision timeline mentioned?
• Other stakeholders who need to be involved?
• Internal champions identified?

Next Steps Discussed:

• Any commitments made by either side
• Follow-up materials requested
• Next meeting scheduled or proposed
• Trial/pilot discussions

Step 3: Map to ICP and Pipeline Stage (Layaa AI Mode)

Using extracted information:

1. Classify the prospect into an ICP category from shared-references/icp-and-market.md
2. Determine current pipeline stage:
   • MQL — Interest expressed but not qualified
   • SQL — Pain confirmed, budget exists, timeline is real
   • Proposal — Active evaluation, proposal requested or sent
   • Negotiation — Terms being discussed
   • Won/Lost — Decision made
3. Assess stage movement: Did this call advance, stall, or regress the deal?
4. Flag if conversion benchmarks are at risk (MQL→SQL 25%, SQL→Proposal 60%, Proposal→Won 35%)

Step 4: Identify Service Package Fit (Layaa AI Mode)

Based on the pain points and requirements discussed:

1. Read domain-references/sales/service-config-matrix.md
2. Match discussed needs to specific service packages
3. Note any scope creep risks (prospect asking for things outside standard packages)
4. Flag if a custom/enterprise package may be needed

Step 5: Generate Action Items

Create a prioritized action list:

Immediate (within 24 hours):

• Send follow-up email (drafted in Step 7)
• Share any materials promised on the call
• Update CRM/pipeline status

Short-term (within 1 week):

• Prepare requested deliverables (proposal, case study, demo)
• Schedule next meeting if agreed
• Loop in additional team members if needed

Strategic:

• Internal alignment needed (pricing approval, technical feasibility check)
• Competitive positioning preparation
• Escalation items for founders

Step 6: Flag Escalation Needs

Determine if any of the following require escalation:

• Founder escalation: Prospect wants to speak with founders, deal size is large (>5L implementation), strategic partnership discussed
• Pricing escalation: Custom pricing requested, significant discount asked, non-standard payment terms
• Technical escalation: Complex integration requirements, security/compliance demands beyond standard
• Risk flags: Prospect seemed disengaged, competitive threat mentioned, timeline slipping

Step 7: Draft Follow-Up Email

Generate a follow-up email that:

1. Thanks them for their time (brief, not effusive)
2. Summarizes the key points discussed (3-5 bullets max)
3. Confirms next steps with specific dates/deadlines
4. Attaches or references any promised materials
5. Ends with a clear single CTA

Tone rules (Layaa AI mode):

• Professional, warm, concise
• No jargon unless the call was technical
• Reference specific things they said to show active listening
• No generic "great chatting" openers

Step 8: Generate Pipeline Update

Create a structured update suitable for CRM entry or team standup:

• Deal name and contact
• Stage change (if any)
• Win probability adjustment
• Key risks
• Next action and owner

Output Format

## Call Summary: [Company Name] — [Date]

### Attendees
| Name | Title | Company | Role in Deal |
|------|-------|---------|--------------|
| [name] | [title] | [company] | [Champion/Decision Maker/Evaluator/Blocker] |

### Call Context
- **Deal Stage:** [stage] → [new stage if changed]
- **ICP Match:** [category]
- **Call Purpose:** [discovery / follow-up / demo / negotiation]
- **Duration:** [if known]

### Key Findings

**Pain Points:**
1. [pain point] — Severity: [Critical/High/Medium/Low]
2. [pain point] — Severity: [Critical/High/Medium/Low]

**Objections:**
1. [objection] — Type: [Pricing/Timing/Technical/Competitive]
   - Suggested response: [from battle card]

**Budget Signals:**
- [budget information extracted]

**Decision Process:**
- Decision maker: [name/title or unknown]
- Timeline: [stated timeline or estimate]
- Other stakeholders: [if mentioned]

### Service Package Fit
- **Recommended package:** [package name from service matrix]
- **Estimated deal size:** [range]
- **Scope notes:** [any adjustments needed]

### Action Items
| # | Action | Owner | Deadline | Priority |
|---|--------|-------|----------|----------|
| 1 | [action] | [who] | [when] | [High/Med/Low] |

### Escalation Flags
- [any items requiring founder or specialist attention]

### Pipeline Update
- **Stage:** [current] | **Probability:** [%] | **Next Action:** [what] by [when]

---

## Follow-Up Email

**Subject:** [subject line]

[email body]

What Makes This Different from Generic Call Summary

• Maps call insights to Layaa AI's specific ICP profiles and conversion benchmarks
• Identifies which service package fits the discussed requirements
• Matches objections to battle-card responses from the sales playbook
• Flags deals against Layaa AI's pipeline conversion rates (MQL→SQL 25%, SQL→Proposal 60%, Proposal→Won 35%)
• Applies Layaa AI brand voice to the follow-up email
• Knows the escalation paths (to founders, to pricing specialist Veer, to legal Abhay)
• Understands the minimum viable budget threshold (50k+ implementation)