Evidence-backed sales call and pipeline workbench

For

Sales managers and revenue operations leads running inside sales teams

Solves

Call insights, deal scoring and follow-up live in separate tools, so coaching and prioritization drift from what buyers actually said.

Delivers

Manager-approved deal priorities and follow-up drafts linked to call evidence

Built in

about 5 weeks of creation time, MVP in 6 days

Investment

$14,000 for the MVP, $47,500 for the full product

Run it

Inside your business, or as part of your offer to clients

Reduce deal review effort while keeping coaching tied to recorded buyer evidence.

1. Sync CRM deal and contact records.
2. Record and transcribe sales calls.
3. Summarize calls with key takeaways.
4. Surface real-time call insights.
5. Flag objections, competitor mentions and key questions.
6. Update scorecards against MEDDPICC, BANT, SPIN or custom playbooks.
7. Adjust scoring for buyer stage and contact role.
8. Tie call scores to deal stage and outcome.
9. Suggest coaching drills per rep.
10. Draft individual development plans.
11. Rank pipeline deals by evidence.
12. Track and forecast pipeline.
13. Score leads from predictive signals.
14. Suggest personalized outreach messages.
15. Draft follow-up emails.
16. Recommend next steps for reps and buyers.
17. Show performance dashboards.
18. Compare the reviewed result with the recorded baseline and value assumptions.
19. Capture corrections and named-owner approval before consequential use.
20. Export a versioned manager-approved deal priorities and follow-up drafts linked to call evidence with source references and unresolved questions.

Everything these tools do, in one app

• CRM integration Connects with CRM platforms to sync sales data and provide context without manual entry.Found in Endgame 2.0, Naoma, Sales AGI and 3 more
• Call recording and transcription Records and transcribes sales calls for later analysis and review.Found in Endgame 2.0, Attention
• Call summarization Generates summaries and key takeaways from sales calls automatically.Found in Endgame 2.0, Oliv: The Next-Gen AI Sales
• Real-time call insights Provides actionable insights during sales calls to help reps make informed decisions on the fly.Found in Naoma, Attention
• Key moment detection Flags critical moments like objections, competitor mentions, and important questions in real time.Found in Naoma
• Scorecard automation Automatically updates sales scorecards using frameworks such as MEDDPICC and BANNT.Found in Oliv: The Next-Gen AI Sales, Playcall
• Methodology-based scoring Scores calls against sales methodologies like MEDDPICC, BANT, SPIN, or custom playbooks.Found in Playcall
• Buyer-aware scoring Adjusts call scoring based on buyer context such as company stage and contact role.Found in Playcall
• Outcome-tied scoring Links call scores to deal stage, outcome, and pipeline impact to show which behaviors correlate with closed deals.Found in Playcall
• Coaching recommendations Provides personalized tips and actionable drills for each sales rep to improve their approach.Found in Naoma, Pod 2.0, Playcall
• Individual development plans Highlights strengths and growth opportunities for each sales representative with structured insights.Found in Naoma
• Deal prioritization Analyzes pipeline data to highlight the most promising deals so reps can focus on high-potential opportunities.Found in Pod 2.0
• Pipeline management Tracks and forecasts sales pipeline in real time.Found in Sales AGI, Pod 2.0
• Lead scoring Automatically scores leads based on predictive analytics to prioritize potential customers.Found in Sales AGI
• Personalized outreach suggestions Suggests personalized outreach messages to improve communication effectiveness with prospects.Found in Sales AGI
• Follow-up email automation Drafts personalized follow-up emails with AI to ensure timely and tailored communication.Found in Attention
• Next step recommendations Provides clear next steps for sales reps and customers to ensure follow-up action.Found in Oliv: The Next-Gen AI Sales, Pod 2.0
• Performance analytics dashboards Monitors team activities and sales outcomes through dashboards.Found in Sales AGI, Attention
• Self-hosting Allows deploying the software on your own infrastructure with no vendor lock-in.Found in Playcall
• Bring your own LLM Supports plugging in multiple LLM providers like Claude, GPT, Gemini through an API key.Found in Playcall

What goes in, what comes out

The workflow

1. In
   Start with

   Licensed call recordings, CRM deal records, sales methodology scorecards and buyer context

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect licensed call recordings

4. 3

   CRM deal records

5. 4

   Sales methodology scorecards and buyer context

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Manager-approved deal priorities and follow-up drafts linked to call evidence

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One fixed CRM schema and licensed call-recording set; final scoring, coaching and outreach approval remain managerial. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Call and pipeline workspace, Editable review preview, Manager proof and delivery. Use a thumbnail gallery for calls and deals, a large central review canvas, and a right-hand panel for evidence, scorecards and comments. Let users compare call versions and scorecards side by side. Display draft, changes requested and approved states. Provide a manager preview link with comments anchored to the relevant call moment. Make the task-specific outcome manager-approved deal priorities and follow-up drafts linked to call evidence visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, call and deal versions, manager comments, approval states, usage allowances, revision limits, download history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Buyer-owned CRM records, authorized call recordings and permitted research sources. Cloud storage, CRM import/export and email destinations. Start with file exchange and validate destination specifications before promising direct sending. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   6 days

   One buyer segment, one recurring use case; first modules: sync CRM deal and contact records; record and transcribe sales calls. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   7 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   3 weeks

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will sales managers and revenue operations leads running inside sales teams use it to solve "call insights, deal scoring and follow-up live in separate tools, so coaching and prioritization drift from what buyers actually said"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Reviewed deals per manager hour and follow-up actions completed after calls.
4. Measure, then decide. Track reviewed deals per manager hour and follow-up actions completed after calls; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One fixed CRM schema and licensed call-recording set; final scoring, coaching and outreach approval remain managerial. Implement one approved input format, a bounded representative case set and the first two task modules: sync CRM deal and contact records; record and transcribe sales calls. Support the third module with operator review: summarize calls with key takeaways. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around manager-approved deal priorities and follow-up drafts linked to call evidence. Retain the explicit scope boundary: One fixed CRM schema and licensed call-recording set; final scoring, coaching and outreach approval remain managerial.

What the build depends on. Call upload and preview, asynchronous processing jobs, editable version history, reviewer access and tested export formats. High-fidelity sales review requires specialist QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One fixed CRM schema and licensed call-recording set; final scoring, coaching and outreach approval remain managerial.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined call and deal package. Offer a monthly production allowance after repeat demand. Quote complex multi-team or custom-methodology work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded manager-approved deal priorities and follow-up drafts linked to call evidence. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce deal review effort while keeping coaching tied to recorded buyer evidence. Demonstrate a concrete manager-approved deal priorities and follow-up drafts linked to call evidence using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Sales managers and revenue operations leads running inside sales teams professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample manager-approved deal priorities and follow-up drafts linked to call evidence from a small authorized input set, with a transparent calculation of reviewed deals per manager hour and follow-up actions completed after calls and no promised savings.

The first 30 days

1. Week 1: interview five sales managers and revenue operations leads running inside sales teams and inspect a recent example of call insights, deal scoring and follow-up living in separate tools, so coaching and prioritization drift from what buyers actually said.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure reviewed deals per manager hour and follow-up actions completed after calls, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Reviewed deals per manager hour and follow-up actions completed after calls. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Reviewed deals per manager hour and follow-up actions completed after calls; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs manager-approved deal priorities and follow-up drafts linked to call evidence. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved scorecards, buyer contexts and review examples, together with reliable delivery for a narrow sales niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for sales managers and revenue operations leads running inside sales teams. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Endgame 2.0, Naoma, Sales AGI, Oliv: The Next-Gen AI Sales, Attention, Pod 2.0 and Playcall, plus manual CRM review and spreadsheet scorecards. Compare this product with the buyer's present method on reviewed deals per manager hour and follow-up actions completed after calls. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Transcription and LLM processing, storage, reviewer hours, manager revision rounds and licensed source material. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of manager-approved deal priorities and follow-up drafts linked to call evidence. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve buyer confidentiality, source attribution, quotation accuracy and usage permissions. Managers approve substantive scoring, coaching and outreach changes. One fixed CRM schema and licensed call-recording set; final scoring, coaching and outreach approval remain managerial. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.