Cleanlist AI vs Superagent: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Cleanlist AI and Superagent — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Cleanlist AI
Cleanlist
AI-powered B2B prospecting and enrichment that turns plain-English prompts into verified, CRM-ready lead lists via a 15-provider waterfall.
Key features
- Conversational List Builder: Describe any target list in plain English and the Co-Pilot returns a fully enriched, CRM-ready set of leads.
- 15-Provider Waterfall Enrichment: Providers compete in real time on every contact to deliver 98% email accuracy and 85% direct-dial find rates.
- Company-First ICP Search: Filter by industry, size, geography, tech stack, hiring signals, and funding stage, then pull every relevant decision-maker.
- LinkedIn & Sales Navigator Extension: Open any profile, click Cleanlist, and get a verified email and direct dial in two seconds.
- CSV Enrichment: Drop 500 rows and each is run through the full waterfall, returning verified emails, direct dials, titles, and firmographics.
- Native CRM Sync: One-click, two-way sync to HubSpot, Salesforce, Pipedrive, Outreach, Salesloft, and lemlist — no Zapier required.
- AI Columns and Smart Agents: AI-generated columns add ICP scoring, company summaries, and competitor notes with the reasoning behind each answer.
Best for
- Outbound Prospecting: Sales reps build targeted lead lists on demand and push them straight to a sequencer.
- RevOps CRM Cleanup: Ops teams re-enrich stale HubSpot or Salesforce records to restore email deliverability and phone connect rates.
- Inbound Speed-to-Lead: Trigger enrichment on new form fills so reps have full context within minutes of a signup.
- ABM Account Expansion: Discover every relevant decision-maker inside a target account list without juggling multiple databases.
- Sales Stack Consolidation: Replace ZoomInfo/Apollo plus a separate email verifier and phone tool with one credit-based platform.
Superagent
Superagent Technologies, Inc.
Open-source AI security platform that provides runtime protection for agents, prevents data leaks, and offers hosted compliance trust centers.
Key features
- Runtime Protection: Real-time interception and inspection of agent prompts and tool calls to detect and stop data exfiltration, malicious inputs, or unsafe behavior before actions are executed.
- Prompt Inspection & Validation: Analyze and enforce policies on prompts and inputs, validate tool-call schemas and parameters, and block or modify calls that violate rules or expose sensitive data.
- Tool Call Firewall & Sandboxing: Validate, allow, or deny external tool invocations and run tools in isolated sandboxes (e.g., Vibekit) to contain risk from third-party models and tools.
- Data Redaction & Sensitive Data Protection: Automatic redaction/masking of PII and secret material in transit and in logs, preventing sensitive data from being stored or leaked to external services.
- Hosted Trust Center & Compliance Artifacts: Generate and host audit trails, dashboards, and compliance proofs that demonstrate runtime protections to enterprise buyers and security teams.
- Multi-language SDKs & High-performance Proxies: SDKs for TypeScript and Python plus proxy implementations in Node and Rust for flexible integration and production-grade performance.
- Observability & Auditing: Detailed telemetry, logging, and audit trails of agent decisions and tool usage to support incident investigation, forensics, and regulatory reviews.
- Deployment Tools & Integrations: CLI, Docker configurations, and docs for straightforward deployment into CI/CD pipelines, staging environments, and production agent stacks.
- Prompt inspection and runtime monitoring of agent interactions
- Tool-call validation and enforcement to block malicious or sensitive operations
- Real-time blocking of threats and prevention of data leaks
- Multiple proxy implementations: Node.js and Rust (high-performance)
- SDKs for TypeScript and Python for programmatic control (agent/tool creation and invocation)
- Command-line interface and Docker configurations for deployment
- Sensitive-data redaction and observability baked into sandboxes (vibekit)
- Hosted trust center for compliance evidence and buyer assurance
- Support for multiple LLM providers (OpenAI, Anthropic, etc.)
- Models and additional resources published on Hugging Face and GitHub
Best for
- Preventing data exfiltration from production agents by inspecting prompts and blocking tool calls that attempt to leak secrets or PII.
- Proving enterprise compliance during vendor security reviews by providing hosted trust center dashboards and audit artifacts that show runtime protections.
- Running third-party LLMs and coding agents in isolated sandboxes to safely evaluate capabilities without exposing sensitive corpora or credentials.
- Instrumenting copilots and agent-based workflows to validate tool-call schemas, enforce business policies, and prevent unauthorized actions programmatically.
- Redacting sensitive customer or internal data before logging or sending requests to external APIs to reduce breach and compliance risk.
- Providing a developer-facing security layer (SDKs + proxies) to integrate policy enforcement and observability into existing agent deployments.
- Protecting conversational agents and copilots from exfiltration and malicious tool calls
- Adding runtime enforcement and validation around third-party tool integrations
- Running coding agents in isolated sandboxes with redaction and observability
- Demonstrating vendor and deployment compliance to enterprise buyers via a trust center
- Embedding SDK-driven agent management (create agents, add tools, invoke agents) in applications
- Self-hosting or containerized deployment using Docker and provided proxies