Continuously improve outputs based on your GTM ground truth.
Cold opener · 48 words
Hi {{first}} — saw {{company}} pushing unified GTM data this quarter. We help teams like yours get cited answers from Gong + CRM without another dashboard. Worth 15 minutes?
- Specificity (their motion / stack)78Pass
- Proof before the ask45Gap
- One clear CTA88Pass
- Outcome / ROI hook32Fail
- Length (≤90 words)92Pass
Fail — No measurable outcome. Won replies tie to a business result in 6 of 10; this stops at “cited answers.”
Integrations
Endpoints
SearchCited answers from your corpus
POST /api/platform/v1/search/query
{
"query": "why do enterprise renewals stall?",
"mode": "blended"
}
→ {
"answer": "Security review at week 6…",
"citations": ["i.4821", "c.19"],
"rows": 38
}Search, evaluate, and optimize against your buyer data.
Driven by statistical learning and causal analysis of what your buyers say, how they progress in your funnel, and what actually works.
0% time saved
Chore's marketing team reclaimed their week after moving content production onto Amdahl
0.0x win rate
Reps surface more first-call objections and close more — measured on our own data
0x viral reach
Multiple Chore posts hit 100,000 impressions against a 1,000 baseline
Search, Evaluate, Optimize
Go-to-market, like an engineer.
Search
- Ground every agent output in what uniquely works in your go-to-market reality, instead of surface-level assumptions.
- Contextual retrieval your agents need: What to say, and to whom.
- Semantic search across what your buyers actually said across your first-party data, not the public web.
Budget freeze is the primary blocker, not product fit. 73% of stalled enterprise deals cite internal budget reallocation. Here's the breakdown:
Budget freeze is the #1 blocker
Concentrated in accounts with renewal dates in Q3. CFO-level freezes on net-new vendor spend above $100K.
Migration cost concerns surface in 12 of 38 stalled deals
Buyers want a managed cutover plan and a fixed-price quote. Existing playbook is Lattice case study.
- Which 38 accounts are affected?
- What did finance say in last week's calls?
- Show me Q3 renewal exposure by segment
- Compare to Q4 last year
0x
token efficiency
Raw MCPs firehose vast amounts of data into every agent call. Instead, Amdahl serves the most relevant context needed.
0.0x
more accurate
Our ML models achieve accuracy and depth that LLMs miss. No human revisions needed.
0.0x
more consistent
100% of LLM outputs cited in your customer intelligence data. No hallucinated insights or statistics.
0 mins
data freshness
5 minutes end-to-end data processing latency.
Evals based on your market truth.
Ship GTM that already passed the evidence bar of what resonates with your buyers. Score agent outputs against how deals actually played out.
Backed by world-class investors
