AI app for sales · no coding needed
Evidence-backed sales call and pipeline workbench
Reduce deal review effort while keeping coaching tied to recorded buyer evidence.
Made for: Sales managers and revenue operations leads running inside sales teams
What it does for you
The problem
Call insights, deal scoring and follow-up live in separate tools, so coaching and prioritization drift from what buyers actually said.
What it gives you
Manager-approved deal priorities and follow-up drafts linked to call evidence
What you give it
Licensed call recordingsCRM deal recordssales methodology scorecardsbuyer context
Build your own version of Endgame 2.0, Naoma and more
One app with what these 7 AI tools do, yours to keep and change: Endgame 2.0, Naoma, Sales AGI, Oliv: The Next-Gen AI Sales, Attention, Pod 2.0, Playcall.
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
How it works, step by step
- Sync CRM deal and contact records
- Record and transcribe sales calls
- Summarize calls with key takeaways
- Surface real-time call insights
- Flag objections, competitor mentions and key questions
- Update scorecards against MEDDPICC, BANT, SPIN or custom playbooks
- Adjust scoring for buyer stage and contact role
- Tie call scores to deal stage and outcome
- Suggest coaching drills per rep
- Draft individual development plans
- Rank pipeline deals by evidence
- Track and forecast pipeline
- Score leads from predictive signals
- Suggest personalized outreach messages
- Draft follow-up emails
- Recommend next steps for reps and buyers
- Show performance dashboards
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned manager-approved deal priorities and follow-up drafts linked to call evidence with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Evidence-backed sales call and pipeline workbench with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Evidence-backed sales call and pipeline workbench with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links5 KB
- questions.mdQuestions to answer before you build3 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare27 KB
- prompt-vps.mdThe same build on your own server (Docker)27 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria14 KB
- demo/index.htmlThe working demo on sample data197 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce deal review effort while keeping coaching tied to recorded buyer evidence. For sales managers and revenue operations leads running inside sales teams, convert licensed call recordings, CRM deal records, sales methodology scorecards and buyer context into manager-approved deal priorities and follow-up drafts linked to call evidence. The benefit is a testable hypothesis, measured through reviewed deals per manager hour and follow-up actions completed after calls; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect licensed call recordings, CRM deal records, sales methodology scorecards and buyer context, then follow this sequence: 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. Resolve uncertain cases with qualified reviewers, approve manager-approved deal priorities and follow-up drafts linked to call evidence, and measure reviewed deals per manager hour and follow-up actions completed after calls against a documented baseline.
How the AI works
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.
Safeguards
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.
What to build first
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.
What it can connect to
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.
The screens in detail
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.
