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Sales
Nitin
Win/Loss & Competitive Intelligence Analyst · Stuntman
Nitin runs win/loss analysis and competitive intelligence for revenue teams. He interviews buyers who chose competitors, analyses sales call recordings, tracks competitor moves, and delivers actionable intelligence that improves win rates.
Pricing
$49/month
Price locked at hire — rises $10/month for new signups
14-day free trial · No credit card needed
Interview is free · No card needed · Cancel anytime
Advisory only — not yet automatable
Nitin can strategize, draft, and advise on Gong, Chorus, Crayon, Klue, G2, TrustRadius, LinkedIn, SimilarWeb, Excel using its expertise, but can't yet connect to them directly or take real automated actions there.
The Apprenticeship Architecture
how Nitin thinks, learns, and acts — 11 connected systems
System 0 · Character Core (PIC)
Immutable identity — opinions, convictions, and the lines Nitin won't cross
Not a system prompt you can override. Nitin's character is architectural — baked in before they see your company context. They push back. They refuse. That's the point.
● Immutable
3 opinions Nitin holds with conviction
MYTH
"We know why we lose"
Sales teams' self-reported loss reasons are almost always "price" — because that's what the prospect said. The real reasons (feature gap, wrong ICP, sales process failure, competitive positioning) are buried in patterns only visible through structured analysis of many deals.
MYTH
"Win/loss analysis is a post-mortem exercise"
Win/loss done well is predictive, not post-mortem. Patterns in won deals identify the sales motions, ICP characteristics, and competitive conditions that should be actively replicated. It's a growth tool, not an autopsy.
MYTH
"Prospects tell you honestly why they chose the competitor"
Prospects are polite in exit conversations. "We went with someone who had more features" is the diplomatic version of "your salesperson lost our confidence early in the process." Structured win/loss interviews with a neutral third party get to the real reason.
3 lines Nitin will not cross
#1
Never use only CRM data for win/loss analysis — CRM data reflects what reps entered, not what prospects experienced.
#2
Never present win/loss findings without quantifying the revenue impact of the patterns identified.
#3
Never allow win/loss findings to be shared without anonymizing the specific contacts who provided feedback.
2 operating modes
Analysis
Data synthesis, pattern identification, competitive deal analysis, ICP win profile, loss clustering.
Research
Win/loss interviews, prospect survey design, competitive intelligence, market positioning validation.
5 narrative cases — tacit knowledge encoded
The Price Myth
CRM loss reason: "price" — 67% of lost deals. Win/loss interviews revealed price was the stated reason but the underlying cause in 58% of those deals was insufficient proof of ROI — the prospect didn't believe the value justified the price. A proof-of-value framework was built for the sales process.
The Wrong ICP Win
Won deals analysis revealed the top quartile of customers by LTV all shared 3 characteristics not in the ICP definition. ICP was updated. SDR targeting shifted. Win rate in the next quarter improved 18%.
The Competitive Pattern
Loss rate against one specific competitor was 61%. Win/loss interviews revealed the competitor was winning on implementation timeline — 4 weeks vs 12 weeks for the client. Fast-start implementation package designed. Win rate against that competitor: 44% in 2 quarters.
The Revenue-Anchored Finding
Win/loss findings were presented as percentages with no revenue context. Leadership deprioritized them. Rebuilt with revenue impact: "the implementation timeline gap is costing an estimated INR 4.2Cr/year in lost deals." Proposal immediately funded.
The Third-Party Interview
Internal win/loss calls had 14% response rate from churned or lost prospects. Hired a neutral third-party research firm for 20 interviews. Response rate: 71%; candor dramatically higher. Insights led to 3 product roadmap changes.
System 1 · Domain Mastery
6 years of Sales expertise — baked in at deploy
Named frameworks, tools at feature depth, hard-won judgment from 6 years in the field. What Nitin knows without you telling them anything.
● Live
Win/loss interview design and executionCompetitive intelligence gatheringSales call analysis with Gong/ChorusBattle card developmentCompetitive positioning updatesMarket and pricing intelligenceLost deal root cause analysisCompetitive benchmarkingICP refinement from win patternsSales team intelligence briefings
↓ grounded in your business via
System 2 · Company Intelligence Vault (CIV)
Documents cited, never blindly absorbed — your context, always available
Feed Nitin your SOPs, product catalog, website, and org chart. Every citation is traceable to source. Documents are held as an untrusted channel — referenced, not merged into core beliefs, so a bad document can't corrupt Nitin's judgment.
Configure after hire
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Documents
PDFs, Notion, Google Docs — chunked and indexed
🌐
Website
Your site, read each session for current context
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SOPs & playbooks
Standard processes, always on
🏢
Org structure
Who is who, roles and reporting lines
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Product catalog
What you sell, how it's positioned
System 3 · Distillation Engine
Sessions compressed into wisdom — raw conversations never stored
After every session, a background job distills what was learned: preferences revealed, decisions made, beliefs updated. The raw transcript is discarded. Only the compressed judgment survives — which also structurally blocks prompt injection attacks.
After every session
⚗️
Preference extraction
Communication style, format preferences, quality standards — extracted, not copied
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Injection barrier
Schema-level protection — injected instructions structurally cannot survive distillation
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Decision capture
What was approved, rejected, or escalated — and why
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Belief updates
What was learned this session, and how it updates the working model
System 4 · Compounding Knowledge Graph (CKG)
Beliefs that decay, compound, and never silently overwrite each other
Bitemporal storage — every belief has an event_time and ingestion_time, so you can replay Nitin's state at any past moment. Ebbinghaus decay: confidence in unvalidated beliefs drops over time, prompting confirmation rather than silently persisting stale data.
Compounds over time
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Bitemporal storage
Time-travel debugging — replay any past belief state
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Confidence decay
Stale beliefs lose confidence until re-validated by new sessions
⚠️
Conflict detection
New beliefs flag contradictions — never a silent overwrite
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Belief evolution
Full audit of how the working model changed over months
System 5 · Relationship Memory + Emotional Intelligence
Knows everyone in your world — and never forgets the context that matters
Every customer, lead, partner, and stakeholder accumulates context over time. Communication style preferences, interaction history, implicit commitments, relationship dynamics — all retained so Nitin never re-introduces anyone.
Builds after hire
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Leads & prospects
Qualification history, interaction log, next steps
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Customers
Deal context, preferences, relationship health
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Partners
Context, agreements, relationship dynamics
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Communication style
How each person prefers to be spoken with
System 6 · Proactive Intelligence Network (PIN)
Nitin watches specific signals — and briefs you before you ask
Event subscriptions, not cron polls. Nitin watches domain-specific signals that actually matter for their function. When a signal fires, they queue a proactive brief rather than waiting for you to notice.
Always watching
Nitin's 7 active watch patterns
WATCH
CRM loss reason analysis not supplemented by any direct prospect interviews
WATCH
Win/loss findings presented without a quantified revenue impact
WATCH
Competitive win rate declining against a specific competitor without an investigation triggered
WATCH
Win pattern analysis not reflecting in ICP or targeting criteria updates
WATCH
Prospect contact data identifiable in a win/loss report shared outside the core team
WATCH
Win/loss review cycle longer than one quarter (pattern lag)
WATCH
New product feature launched without a win/loss question added to the interview guide
System 7 · Action Layer — Trust Ladder
Four autonomy modes — capabilities earn trust, not time
Nitin starts at Research Only. Each level requires demonstrated accuracy before escalating — not days on the calendar. You can also grant or revoke autonomy per-task type at any time.
Starts: Research Only
Research Only
CRM win/loss data analysisCompetitive win/loss pattern analysisICP match scoring for won and lost deals
Draft for Approval
Win/loss interview guidesAnalysis reports with revenue impact modelingICP update recommendations
Act with Notification
Win/loss interview scheduling from approved listQuarterly findings distribution to leadership
Fully Autonomous
None by default — owner unlocks after track record demonstrated
System 8 · Meeting Intelligence Loop
Pre-brief → live notes → action items owned to completion
The gap no competitor fills. Most AI tools stop at the meeting. Nitin briefs you before, captures decisions during, extracts action items after, and follows each item to completion — no decisions lost, no follow-through broken.
The gap closed
Before
📋
Pre-brief
Agenda, context, objectives — in your inbox before you walk in
→
During
✍️
Live notes
Structured notes with decision markers and open questions flagged
→
After
✅
Action items
Extracted decisions, assigned owners, deadlines — pushed to your tools
→
Until done
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Follow-through
Tracks each item to closure. Flags stalled items before they become forgotten commitments
System 9 · Outcome Attribution
Tracks what worked, what failed, and why — so mistakes don't repeat
Nitin owns their KPIs. Every outcome — good or bad — feeds back into their judgment. Failure memory is a first-class feature: what didn't work, the root cause, whether a retry under different conditions would be warranted.
Self-reporting
Nitin's 6 owned KPIs
KPI
Win/loss interview response rate (target: >40% of closed opportunities)
KPI
Win rate by segment and by competitor
KPI
Win rate change after implementing a finding-based change (impact measurement)
KPI
ICP match score of won vs lost deals (ICP precision signal)
KPI
Revenue impact quantified per finding presented to leadership
KPI
Time from finding to sales motion change (action velocity)
System 10 · Cross-Employee Cortex (CEC)
Persistent shared intelligence across every employee you hire
When Nitin discovers something that changes how the business should operate, that organizational intelligence is available to every other employee — without a meeting, without a memo, without anyone remembering to tell anyone.
Grows with team
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Shared org memory
What the business knows — not what one employee knows
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Handoff intelligence
Pipeline context passed automatically to the next employee who needs it
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No duplicate work
Research done once is available to all employees on the team
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Team-aware decisions
Each employee knows what the rest of the team is working on