Clay vs Orange Slice (2026)

Clay

by Clay

Orange Slice

by Orange Slice

Pros

• ✓Waterfall enrichment across a marketplace of 200+ data and AI vendors queries sources in sequence and stops at the first verified match, which widens coverage while holding credit cost down, and failed enrichments consume nothing.
• ✓Claygent reads any webpage and extracts the data points you specify, so a careers page yields open roles, headcount and tech-stack signals that no pre-indexed provider holds, pushed straight into your CRM in the same workflow.
• ✓A first-party MCP server lets ChatGPT, Codex and Claude call Clay Functions and reason across Audiences directly, with write rules defined by the operations team rather than by the assistant.

Limitations

• –The dual-meter model of Data Credits and Actions makes cost forecasting genuinely hard. Claygent runs and multi-provider waterfalls consume credits at variable rates, and frontier-model usage is billed on actual token consumption.
• –The platform rewards a dedicated owner. Building effective waterfall tables and Claygent prompts requires understanding data-provider coverage, API logic and prompt construction, which is a real investment for a non-technical team.
• –Data freshness depends on the underlying providers rather than on Clay, since it aggregates third-party sources rather than maintaining its own database. Phone number coverage is inconsistent across the marketplace.

Pros

• ✓Plain-English requests find and enrich companies and people, with waterfall enrichment across many providers and no charge when a work email or phone lookup finds nothing.
• ✓Runs from a sheet, a chat agent, an API, or Claude Code through its CLI or MCP, and pushes leads to HubSpot, Salesforce or Attio.
• ✓Published per-lookup prices, vendor cost with no markup on Pro, and unused balance that rolls over, with plans that can be cancelled at any time.

Limitations

• –No SOC 2 audit completed yet, per Orange Slice's own security page.
• –There is no free plan: every plan needs a card, and pay as you go adds 25% to each lookup and has no chat agent or sequencer.
• –Usage is billed per lookup, so costs grow with list size and need modelling before large enrichment runs.