A GTM optimization model, through one API.
Buyer insights.
Who wins, what resonates, and why buyers need you, answered from your own calls and CRM, with the quotes.
Example runs of the Amdahl API on sample data. Each question returns cited evidence. Each draft returns its checks.
Where did security reviews stall deals last quarter?. Result: 23 matches · 3 stall patterns. Deals citing: SOC 2 timing / bridge letter 14, Legal redlines on DPA 6, Pen-test evidence ask 3, SSO scoping 2. 14 deals cite SOC 2 timing — not price. The stall is paperwork, not conviction. Avg 24 days lost in the security loop; front-load the packet at Eval entry.
Which open deals have a champion who went quiet in the last 30 days?. Result: 9 deals · $1.4M at risk. Days silent: Vantiv · expansion 41, Corex · new logo 36, Helio · renewal+ 33, Braxton · new logo 31, Nimbus · expansion 30. 3 of 9 mentioned a reorg on their last call — champion risk, not deal risk. Re-engage Vantiv first: $320K and the EB was never multi-threaded.
What made buyers switch to us from Vectorline this year?. Result: 31 wins · 4 switch triggers. Wins citing: CRM + calls in one query 13, Cited, checkable answers 8, Agents can query it 6, Seat-price fatigue 4. Price is the 4th reason, not the 1st — lead battlecards with unified query, not cost. “Cited answers” shows up in 26% of switch stories; make it the demo's first beat.
Who offered discounts before the buyer even asked?. Result: 17 deals · $340K left on the table. Est. leakage ($K): T. Nguyen 126, L. Marsh 88, D. Okafor 67, K. Silva 41, P. Reyes 18. 16 of 17 concessions came inside 5 minutes of a budget mention — a reflex, not a strategy. Coach the pause: deals with no unprompted discount closed at the same rate.
Which renewals are quietly at risk — and what did the customer actually say?. Result: 6 flagged · 2 critical. Risk severity: Ferrous 91, Lumina 84, Paloma 62, Kestrel 58, Orchid 54. Ferrous said “consolidating vendors” in the QBR — nobody logged it in CRM. 2 critical accounts share one pattern: sponsor change + usage dip. Escalate both this week.
Evaluate + Optimize.
Draft
Your agent writes
Checks
2.6/ 5
Prompt fix
Misses become fixes
Next run
4.2/ 5
Amdahl evaluates drafts against your buyers and optimizes the prompt behind them. Your team stops reviewing every draft by hand.
Eval · Landing hero · headline + sub · 18 words
Draft under test
“Stop guessing. Start knowing. The AI-native revenue intelligence platform that turns every conversation into pipeline you can trust.”
Buyer-language match (%)
| Phrase | Buyer-language match (%) |
|---|---|
| “revenue intelligence” | 2 |
| “AI-native” | 6 |
| “pipeline you can trust” | 31 |
| “every conversation” | 44 |
| “Stop guessing” | 27 |
Phrase match
- Replace
“revenue intelligence”
Buyers say “why deals stall” · corpus 2%
- Replace
“AI-native”
Buyers say “can my agent query it” · corpus 6%
- Close — sharpen
“pipeline you can trust”
Buyers say “answers I can check” · corpus 31%
- Keep the idea
“every conversation”
Buyers say “calls + CRM together” · corpus 44%
- Concretize
“Stop guessing”
Buyers say “stop re-listening to calls” · corpus 27%
60 won-deal quotes · 12 cited · 4 shown
POST /api/platform/v1/evals/runWire it upOne API, over MCP or REST.
It works in Claude, Cursor, or your own runtime.
How it runs: a lead comes in, your agent asks Amdahl what matters to this buyer and gets cited quotes, drafts with your own model and prompt, Amdahl checks the draft, and your agent ships only a pass, for example 4 of 5 checks.
Get started.
Getting started: optionally connect sources such as Gong, HubSpot, and Salesforce; install the API or the MCP server at https://app.amdahl.ai/mcp; then let your agent run. Each draft comes back graded, with the fix, so your agents improve every run.
01
OptionalConnect your data
One-click connect to Gong, HubSpot, Salesforce.
30+ integrations
02
Install the API or MCP
Your team uses the MCP. Your agent calls the API.
claude mcp add --transport http amdahl https://app.amdahl.ai/mcp03
Let your agent run with it
Each draft comes back graded, with the fix.
Agents that improve every run
Explore other use cases for Amdahl with your agent.
What can I use Amdahl for?Tell me some use cases for amdahl.ai, based on what you know about my work. You can use https://amdahl.ai and https://docs.amdahl.ai for reference.








