Can I just use Claude directly on my Gong transcripts?

You can, and most teams do for the first few weeks. You will hit the context wall. Three hundred calls is roughly 800K tokens, frontier models reason effectively over 30 to 60 percent of their window, and the "lost in the middle" problem drops accuracy on content that sits away from the edges of the prompt. What that means in practice: the agent sounds confident, but the answers are a recency-biased sample. Amdahl pre-processes the corpus and scores drafts against it — so Claude writes against 2K tokens of clean signal instead of 800K tokens of raw text. Same agent, a real eval underneath.

Does Amdahl run on Claude under the hood?

Most of Amdahl's internal research and generation flows are routed to Claude — Haiku, Sonnet, or Opus depending on the job. We think Claude is the best general-purpose model for that work. What Amdahl adds is the enrichment, classification, clustering, and draft scoring that turn raw GTM data into an eval any frontier model can call. You can bring your own model via MCP and the same architecture applies.

How does Amdahl's MCP server work with Claude Code and the Agent SDK?

Amdahl ships an MCP server out of the box. Drop the server URL into Claude Code's config, Claude Desktop, or your custom Agent SDK build, and the agent gets tools for scoring drafts and querying evidence: search by persona, filter by deal stage, retrieve quotes by objection type, run the eval. Every tool response includes citations. You do not need to re-train or re-architect your agent — it just gains an eval.

Is Amdahl competing with Anthropic?

No — and we'd feel weird claiming we were. Anthropic ships the frontier model and the runtime. We ship the vertical eval for GTM. Our best outputs depend on a great model underneath us, and your Claude agents' best drafts depend on an honest score underneath them. Both things are true at once. It's complementary by design, not marketing spin.

We already built our own pipeline over Claude. Do we need Amdahl?

Honestly — maybe not, if your pipeline actually handles ingestion from Gong, Fathom, CRM, and support, runs per-utterance classification, scores drafts against won and lost deals, and maintains a citation graph. If someone on your team owns all of that and it keeps working, you've built what Amdahl is. Most teams who tell us they have this discover they have a RAG wrapper over Gong transcripts and a few prompts. Those are the teams that come back six months later. If you'd rather not carry that maintenance burden, we'll handle it.

What if Anthropic ships the GTM workflow themselves?

Horizontal platforms rarely ship the depth a vertical eval needs. Anthropic's roadmap is the model, the runtime, and the agent SDK — not the classifiers, clustering, ontology, and draft scoring specific to GTM conversation data. The pattern of "general-purpose LLM provider plus a vertical eval on top" is stable across nearly every agentic workflow category. The safer assumption is that Anthropic stays horizontal and vertical systems like Amdahl own the draft-vs-customer-evidence job for GTM.

Who is the buyer for Amdahl vs Claude inside our company?

Claude is almost always bought by engineering, an AI platform team, or individual developers expensing Claude Code. The budget is engineering budget. Amdahl is bought by the GTM Engineer, Head of Product Marketing, RevOps lead, or a founder running GTM directly. The budget is GTM budget. The buying committees rarely overlap — which is part of why these two tools coexist without a budget fight.

Amdahl vs Claude

Claude drafts and reasons. Amdahl is the eval it runs against your customer evidence over MCP.

If you're running Claude on GTM work, you're already doing the hard part. Claude Code, the Agent SDK, and custom agents are great at drafting, reasoning, and tool-calling. We run most of Amdahl's own flows on Claude. We're fans, not competitors.

Claude does not ship with an eval against your customer conversations. Amdahl is that layer: score messaging, content, and outbound against won, lost, and stalled deals, with citations, exposed over MCP in a few lines of config.

The objection we hear most is "can't we just paste our transcripts into Claude?" You can, for a few weeks. Then the context window fills, accuracy drops on the quotes that matter, and the model sounds confident on thin evidence. That is a data and eval problem. Amdahl handles it so Claude can write.

The one sentence version

Claude drafts. Amdahl evals.

If you already run Claude on GTM work, Amdahl is the missing eval underneath.

Side by side

Dimension	Amdahl	Claude
Category	GTM eval layer over customer evidence	General-purpose frontier agent and developer platform
What it is	Score drafts against structured conversations with citations, via MCP	LLM plus agentic runtime — Claude Code, Agent SDK, and custom agents
What it reads	Raw Gong, Fathom, HubSpot, Salesforce, Zendesk, Slack customer channels	Whatever you hand it — prompts, files, tool outputs, MCP server responses
ML enrichment on inputs	Per-utterance sentiment, persona, deal stage, objection type, competitive mention, quality score	None at ingestion — the model reasons over whatever tokens you send it
Context strategy	Pre-processed, clustered, and indexed before any agent sees it — 2K tokens of signal	Depends on what you feed it — 800K tokens of raw transcripts hits context rot
Grounding and citations	Every score cites the exact call, timestamp, and speaker it came from	Grounding is only as good as the tool output you hand it — raw transcripts yield vibes-level citations
Agent access pattern	MCP server by default — Claude, ChatGPT, or custom agents run the eval in a few lines of config	Calls Amdahl (or any MCP server) as a tool. Your agent, your orchestration.
Primary buyer	GTM Engineer, Head of Product Marketing, RevOps lead	Engineering, AI platform team, or individual developer
Relationship	Complementary — Amdahl is the eval Claude agents call	Complementary — Claude is the agent that drafts; Amdahl scores
Pricing model	Platform subscription plus per-conversation ingest and enrichment cost	Per-token API usage, Claude.ai subscription, or Claude Code subscription

Claude details from anthropic.com, Claude Agent SDK docs, and Claude Code CLI documentation. Reviewed 2026-04-21.

When to buy Amdahl

01
You need to score GTM drafts against customer evidence with citations
02
Your team is hitting context rot feeding Gong transcripts straight into Claude
03
You want MCP-ready evals without building the pipeline yourself
04
The buyer is the GTM org, not engineering

When to buy Claude

01
You are building an agent or workflow outside GTM (code, infra, docs, ops)
02
You want the raw frontier model and runtime, not a vertical eval
03
Engineering owns the budget and the agent surface
04
The data you need is your codebase, not your customer conversations

Where they split

01
You're wiring Claude to Gong and need an eval, not more transcripts
You gave Claude access to your Gong workspace. It searches transcripts well, pulls clips, summarizes calls one at a time. But ask it to score a hero line or battle card against lost enterprise deals, and you either wait forever, get a plausible pattern from a handful of calls, or get told the answer is in the data but the corpus does not fit. A bigger context window will not fix this. What you need is an eval layer that classifies every utterance and scores the draft before the agent ever sees raw dumps. That is Amdahl. Claude stays your writer.
02
Developer building a custom agent that has nothing to do with GTM
You are building an agent that writes code, manages infrastructure, drafts documentation, or automates a back-office workflow. The data you need is your codebase, your cloud console, your ticketing system. You do not need a GTM eval. You need Claude, the Agent SDK, and whatever MCP servers expose your actual domain. Amdahl is for scoring GTM drafts against buyer conversations. If the workflow is not that job, Amdahl is not the layer you are missing.
03
You already run Claude and want drafts scored before they ship
Your PMM is drafting in Claude. Your RevOps team is prototyping agents. Your content lead is in Claude Code. Point those agents at Amdahl's MCP and Claude stays the same — but every draft can be scored against customer evidence with citations. Claude drafts. Amdahl evals.

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See Amdahl on your own data.

Try it for free

claude plugin marketplace add amdahlco/amdahl-cookbook; claude plugin install amdahl-gtm@amdahl-cookbook

Once Amdahl is connected, see what you can try first