Agentic Index
DeepKeep vs Repello AI (2026)
DeepKeep and Repello AI both test the customer's AI apps and agents and guard them at runtime, and they sit close on the grid, 8.5 and 8 of 14. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
DeepKeep's Reddy agent plans attack paths and pauses for the security team at key decisions, its AI Firewall logs every interaction, and it deploys from SaaS to air gapped. Repello's ARTEMIS runs parallel, multi turn attacks through APIs and the browser and maps findings to MITRE, OWASP, NIST, ISO 42001 and the EU AI Act; ARGUS guardrails log every call, Workstation Lens finds agents on endpoints, and several open source tools are free. Neither publishes a price. On the grid DeepKeep is Full on deployment and human oversight where Repello is None and Partial; Repello is Full on its API and workflow orchestration where DeepKeep is Partial. Choose DeepKeep for steerable testing and deployment control; choose Repello for framework mapped findings and a developer toolkit.
On the Agentic Index AI SOC ranking, neither DeepKeep nor Repello AI clears the bar, which asks for all five investigation loop capabilities documented in full. DeepKeep does not document workflow orchestration in full; Repello AI does not document human oversight and guardrails in full. 23 of the 85 vendors in the lane clear it. See the AI SOC ranking
On the Agentic Index agent infrastructure ranking, neither DeepKeep nor Repello AI clears the bar, which asks for all five production contract capabilities documented in full. DeepKeep does not document security and identity governance in full, nor model flexibility and routing; Repello AI documents two of the five in full. 34 of the 186 vendors in the lane clear it. See the agent infrastructure ranking
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. DeepKeep and Repello AI are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 956 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose DeepKeep if
- Deployment must be documented in full, up to air gapped; Repello is None there.
- The team should steer the red teaming agent at key decisions.
- An inline firewall should log every interaction.
Choose Repello AI if
- Findings should map to MITRE, OWASP, NIST, ISO 42001 and the EU AI Act.
- Agents running on employee endpoints need discovering.
- Free open source tools and a GitHub Action help you start.
| At a glance | DeepKeep | Repello AI |
|---|---|---|
| Category | Security / SOC agent | Security / SOC agent |
| Entry price | Contact for pricing | Contact sales; no prices published. Open-source tools are free. |
| Free / trial | No free tier or trial published. A Scan your Agent form offers an agent attack surface scan but it routes to a submission form rather than self serve access. | Free open-source tools (Whistleblower, Agent-Wiz, Artemis GitHub Action); platform demo on request. |
| Pricing confidence | contact only | contact only |
| Feature | D DeepKeep |
R Repello AI |
|---|---|---|
| Action & orchestration | ||
|
Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
Full / Explicit | Full / Explicit |
|
Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
Partial | Full / Explicit |
|
Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
Full / Explicit | Full / Explicit |
| Knowledge & context | ||
|
Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
Partial | Partial |
|
Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
No / Not documented | No / Not documented |
| Control & trust | ||
|
Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
Full / Explicit | Partial |
|
Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
Partial | Partial |
|
Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
Full / Explicit | Full / Explicit |
|
Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
Full / Explicit | No / Not documented |
| Solution readiness | ||
|
Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
Partial | Partial |
| Platform extensibility | ||
|
Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
No / Not documented | No / Not documented |
|
APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
Partial | Full / Explicit |
|
Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
Full / Explicit | Full / Explicit |
| Specialist automation | ||
|
Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
No / Not documented | No / Not documented |
Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | D DeepKeep |
R Repello AI |
|---|---|---|
|
Entry price Lowest public entry point |
Contact for pricing | Contact sales; no prices published. Open-source tools are free. |
|
Pricing confidence How public the numbers are |
Contact only | Contact only |
|
Billing Primary billing axis |
Not published. No seat, token, interaction or scan unit disclosed anywhere retrieved. | Inference, not stated by the vendor: AI systems under red teaming and runtime protection, and endpoints covered. |
|
Variable cost Workload / overage exposure |
Medium variable cost | Medium variable cost |
|
Free tier / trial Try before you buy |
No free tier
|
No free tier
|
|
Buying motion Self-serve vs sales call |
Sales call | Sales call |
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