Clay builds the machine.
Salmon is the machine.
Clay is powerful — if you have an ops team to run it. Salmon is the research engine for teams who want the answer, not the tooling.
Clay is a platform you build on. Salmon is what you'd build.
Clay is genuinely impressive infrastructure for data enrichment workflows. But "infrastructure" is the key word. Clay gives you the pipes — you still have to design the plumbing, buy credits for every source, and maintain it when things break. Salmon ships the finished thing.
What you're signing up for
What it actually takes to run Clay at scale
- 1 Pick and configure your data sources (Apollo, Hunter, Clearbit...) + credits each
- 2 Build enrichment waterfall logic in Clay's table interface
- 3 Write Claygent prompts for AI-assisted research steps
- 4 Monitor source quality and handle API rate limits and failures
- 5 Rebuild workflows when sources change or go down
- 6 Output quality is bounded by the sources you configured
What you actually do
The full workflow, handled end-to-end
- 1 Describe what you need — in plain language or upload a CSV
- 2 Salmon's AI orchestration layer, selects and sequences the right sources automatically
- 3 Multi-source triangulation across open web, partner APIs, and your data — in one pass
- 4 Recursive reasoning resolves conflicts. Every output confidence-scored.
- 5 Results delivered to CRM, API, or CSV. Done.
You have a technical ops team and want full control
If you have a Clay power user and want to custom-build your enrichment stack across 50+ sources, Clay's flexibility is hard to beat. You get granular control over every step.
You want research outcomes, not infrastructure
If you'd rather describe what you need than configure how to get it, Salmon is faster, simpler, and more consistent. No workflow to build. No credits to track. Just answers.
You're already deep in the Clay ecosystem
If your outbound stack is built on Clay workflows, switching costs are real. Staying makes sense if it's working for you.
Your research questions are complex or compliance-related
KYC/KYB, sanctions checks, adverse media, executive diligence — these aren't Clay's primary use case. Salmon was built for multi-step reasoning across diverse sources.
You need predictable costs at scale
Clay's per-credit model can surprise you when queries hit expensive sources multiple times. Salmon's flat pricing means no credit anxiety and no surprise invoices.
Multiple teams need to use the data
Clay workflows are typically owned by one ops person. Salmon is usable by SDRs, RevOps, marketing, and compliance — no configuration knowledge required.
Different tools for a different mindset.
Clay is a genuinely great product — it's popular for good reason. It gives technical operators incredible flexibility to build exactly the enrichment stack they want.
But Clay puts the work on you. Every query you run through Clay is the result of workflows your team designed, sources your team selected, and logic your team maintains. The output is only as good as what you built.
Salmon is opinionated by design. You describe what you need. Salmon's AI engine figures out the rest — which sources to use, how to resolve conflicts, how deep to go. You're buying the research, not the research tools.
The best analogy: Clay is the kitchen. Salmon is the chef. Both make food. One of them requires a lot more from you.
Yes. Some teams use Clay for outbound workflow orchestration and Salmon as a data source within those workflows via API. They complement each other if your team has the ops capacity for Clay.
Fundamentally different. Clay requires building and maintaining enrichment workflows. Salmon requires describing what you need. If you have a dedicated ops person, Clay's flexibility is powerful. If you want answers without infrastructure, Salmon is simpler by design.
Clay charges per credit, per row, per source — costs scale with complexity. Salmon is flat monthly pricing with unlimited research queries. For teams running complex, multi-source enrichment, Salmon is typically more predictable and often less expensive.
Clay's output quality depends on which sources you configure and how well your waterfall logic handles conflicts. Salmon's AI orchestration automatically selects the best sources, triangulates across them, and confidence-scores every output. Quality is built in, not bolted on.
Yes — KYC, KYB, AML screening, adverse media checks, and sanctions screening are core Salmon use cases. Clay wasn't designed for compliance workflows and lacks the built-in reasoning and audit trail these use cases require.
Skip the build.
Get the answer.
Show us a research question your team has been solving manually or through Clay. We'll show you what Salmon does with it in real time.