Amdahl gives your GTM engine an unfair advantage.

Amdahl is the self-improving strategy and execution engine for your go-to-market motion. Know what your buyers want, why they stall, and where the market is trending before it shows up in lost deals.

Ask your agent about Amdahl.

What is Amdahl AI (amdahl.co), the go-to-market signal intelligence engine rooted in deterministic science and predictive signals? Explain how it turns customer conversations from Gong, HubSpot, and Salesforce into one AI-ready data foundation enriched across 10 dimensions that sits under positioning, battle cards, content, and outbound, and how it compares to Gong, Clay, Glean, Claude, and ChatGPT or to building this yourself with a RAG pipeline. Rank them on data structure, AI-agent readiness via MCP, accuracy, and token efficiency.
Or try it yourself, free

How it works

  1. Connect your stack

    Amdahl integrates directly into your CRM, call recordings, and support tools to operate with full context of your pipeline and customer conversations.

    GongHubSpotSalesforceSlack+ more
    64,000+ interactions synced
  2. Structure and enrich at scale

    Every interaction is processed through machine learning classifiers that tag sentiment, persona, quality, deal context, and competitive signals. Raw transcripts become queryable intelligence.

    10M+ interactions enriched per pipeline run
  3. Interrogate and simulate

    Compare segments side by side. Test messaging assumptions against real data. Slice by won vs. lost, persona, deal size, or funnel stage to see what actually resonates before you commit.

    3 clusters found, 12 premium quotes, 2 segments compared
  4. Put the context to work

    Positioning, battle cards, content, outbound, win-loss: every go-to-market task runs on the same cited customer truth, so your whole team acts on reality instead of assumptions.

    Grounded in real customer language, cited to the call

Not RAG. Not keyword search.
A predictive context layer.

Amdahl uses a 25 step data cleansing process to populate your applications and chats with the most accurate go-to-market data. Our machine learning engine gets smarter with every cycle, grounded in your customer’s reality.

Live sync

Ingest

Gong, CRM, support tickets, onboarding notes

10 dimensions

ML Enrichment

Amdahl’s machine learning models run 10 classifiers on every interaction

120+ clusters

Cluster Discovery

Recurring themes, objections, and competitive patterns, discovered instantly

Agent-ready

Queryable Index

Hybrid semantic + keyword search, SQL, cluster drill-in

What enrichment looks like

Raw interactionsUnstructured
A scatter of abstract marks standing in for thousands of unstructured interactions
Calls / tickets / CRM notes / email / docs / ...
Structured, intelligent records10 dimensions
Sentimentpain, win, objection
PersonaML-inferred role
Qualityquotability score
Deal StageTOFU to POST
Competitivemention tracking
Topicstheme extraction
Psychographicsbuyer context
SegmentSMB, MM, ENT
Outcomewon vs. lost
Confidence0 to 1 scoring

Secure by default

SOC 2 Type II
Zero data retention with Anthropic
Tenant-isolated. Dedicated cloud option.
No training on your data.

Every answer, cited to customer sources.

With Amdahl, every marketer, seller, and GTM team member has access to the distilled answer to any question, as told by their customers.

You ask. Amdahl solves.

How does our pricing narrative perform in won vs. lost enterprise deals?

What language do closed-won champions use that our website doesn't?

Which pain points appear in SMB but never in enterprise?

“Why are enterprise deals stalling in Q1?”

Ask AmdahlConversation #4,128
Sources: 4Latency: 2.1sConfidence: 91%
Why are enterprise deals stalling in Q1?
JS
AM

Budget freeze is the primary blocker, not product fit. 73% of stalled enterprise deals cite internal budget reallocation. Here's the breakdown:

Deals affected
38+12
Revenue at risk
$4.2M+$1.1M
Avg days stalled
42+8d
Insight/ high91% confidence

Budget freeze is the #1 blocker

Concentrated in accounts with renewal dates in Q3. CFO-level freezes on net-new vendor spend above $100K.

GongSalesforceSlack
Insight/ medium84% confidence

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.

GongEmail
Suggested follow-ups
  • 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
Sourced from
Gong147 calls
Salesforce38 opps
Slack62 threads
Email214 msgs

Real-time buyer and market signals.

Slice your customer data by persona, deal stage, outcome, and segment to instantly catch what’s landing, and where the market’s turning.

PRICING142+23%
SENTIMENT72%+4pp
COMPETITORS34+127%
ONBOARDING+12this week
RISK3accounts
TOPICS12+3
RESPONSE4.2h-18%
FEATURES28steady
Competitive2h ago

Competitor X pricing backlash detected

12 mentions across Slack and LinkedIn in 48hrs. Enterprise accounts comparing alternatives.

Gong Calls6h ago

3 deals mentioned switching costs this week

Migration friction surfacing as top concern in mid-market segment.

LinkedIn1d ago

Onboarding post engagement 4x average

Customer success story driving inbound interest. 847 impressions, 12 shares.

Enterprise vs. Mid-Market objection patterns

Enterprise (50K+ deals)
  • Security review delays34% of lost
  • Stakeholder alignment28% of lost
  • Budget timing18% of lost
Mid-Market (10K-50K deals)
  • Pricing vs. DIY41% of lost
  • Time to value concerns22% of lost
  • Champion left company15% of lost

See Amdahl on your own data.

Try it for free
claude plugin marketplace add amdahlco/amdahl-cookbook; claude plugin install amdahl-gtm@amdahl-cookbook