Agentic Index
DeepKeep vs Mindgard (2026)
DeepKeep and Mindgard both run continuous automated red teaming against complete AI systems rather than testing a model in isolation, and the difference is what happens after a finding.
Mindgard is offense specialised: reconnaissance maps the production attack surface across guardrails and system prompts, and an expert services layer sells red teaming as a service alongside the platform, so the output is an attacker's view you take to whoever owns remediation. DeepKeep closes the loop inside one product, translating red team findings into rules enforced by an AI Firewall carrying more than sixty contextual guardrails that can block, redact or alert per policy. One caveat that belongs in both evaluations: DeepKeep documents strong product security but no SOC 2 or ISO 27001 attestation or trust centre could be found, which is a fair question to put to any security vendor.
Choose DeepKeep if
- You want findings to become enforced guardrails in the same product rather than a report.
- Air gapped, on premises or private cloud deployment is a hard requirement.
- Your agent estate includes low and no code builders such as n8n, CrewAI, Make and Dify.
Choose Mindgard if
- You want an attacker aligned view of the production attack surface, mapped independently.
- An expert services layer alongside the platform matches how your team buys testing.
- You already run enforcement elsewhere and need offense to stay a separate function.
| At a glance | DeepKeep | Mindgard |
|---|---|---|
| Category | Security / SOC agent | Security / SOC agent |
| Entry price | Contact for pricing | Contact sales |
| 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. | Not published |
| Pricing confidence | contact only | contact only |
| Feature | D DeepKeep |
M Mindgard |
|---|---|---|
| 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. |
Full / Explicit | 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. |
Partial | Partial |
| 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. |
Full / Explicit | Full / Explicit |
|
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 | Partial |
| Solution readiness | ||
|
Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
Full / Explicit | 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. |
Partial | No / Not documented |
|
APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
Full / Explicit | 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 | Partial |
| 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 |
M Mindgard |
|---|---|---|
|
Entry price Lowest public entry point |
Contact for pricing | Contact sales |
|
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. | scope of AI models, agents, and applications under continuous testing, plus expert services |
|
Variable cost Workload / overage exposure |
High 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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