Agentic Index
Knostic vs SGNL (2026)
Both control what an agent or assistant is allowed to reach, at different layers, 7.5 and 6.5 of 14.
Knostic works at the knowledge layer, preventing enterprise assistants like Microsoft 365 Copilot, Glean and Gemini from oversharing, capturing per user per topic need to know policies, simulating real employee queries to find oversharing before users do, and enforcing with runtime redaction and forensic audit trails aligned to the EU AI Act, ISO 42001 and NIST AI RMF. SGNL works at the identity layer, delivering context aware authorization and zero standing privilege for human, non human and agent identities with an MCP Gateway governing tool use. Knostic stops the answer leaking; SGNL stops the access existing.
Choose Knostic if
- Copilot or Glean oversharing is your live problem and identity controls have not fixed it.
- Simulating employee queries to find exposure before staff do is the proactive control you want.
- EU AI Act, ISO 42001 and NIST AI RMF alignment maps to your compliance obligations.
Choose SGNL if
- Zero standing privilege across human, machine and agent identities is the model you are moving to.
- An MCP Gateway governing which tools agents may use fits your architecture.
- Authorization belongs in identity infrastructure rather than in a knowledge layer above it.
| At a glance | Knostic | SGNL |
|---|---|---|
| Category | Security / SOC agent | Security / SOC agent |
| Entry price | Contact sales | No public pricing; enterprise contracts are quoted through sales |
| Free / trial | Copilot Readiness Assessment offered as an entry point | No free tier or trial is documented on retrieved pages |
| Pricing confidence | contact only | contact only |
| Feature | K Knostic |
S SGNL |
|---|---|---|
| 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 | Partial |
|
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. |
Full / Explicit | Partial |
|
Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
Partial | No / Not documented |
| Control & trust | ||
|
Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
Partial | 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. |
No / Not documented | 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. |
No / Not documented | No / Not documented |
| 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. |
Partial | No / Not documented |
| 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 | K Knostic |
S SGNL |
|---|---|---|
|
Entry price Lowest public entry point |
Contact sales | No public pricing; enterprise contracts are quoted through sales |
|
Pricing confidence How public the numbers are |
Contact only | Contact only |
|
Billing Primary billing axis |
scope of enterprise AI assistants and knowledge sources under governance | enterprise contracts, structure not publicly documented |
|
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 |
CrowdStrike announced an agreement to acquire SGNL in January 2026. Weigh the roadmap, pricing and packaging implications of that acquisition alongside the capability comparison.