Declaw vs RiskKernel

Declaw and RiskKernel are both guardrails & safety tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Declaw

Each agent execution runs inside a hardware-isolated microVM with a warm-pool restore measured in milliseconds. Outbound traffic passes through a per-sandbox proxy the agent cannot bypass, enforced at both L3/L4 and L7 — so if your allowlist says api.openai.com only, evil.com gets blocked and logged automatically. The credential vault injects secrets at the proxy layer, meaning API keys never enter the VM itself. Where Declaw shows its limits: there is no self-hosted option, so teams in air-gapped environments or with data-residency requirements that preclude third-party cloud infrastructure hit a hard wall. Those teams look at building their own Firecracker wrapper.

RiskKernel

Deployed as a single Go binary, it sits in front of your existing OpenAI, Anthropic, or LangChain stack via a one-variable proxy — no rewrite required. Every call is metered and checkpointed, so a killed or crashed run resumes from the last saved state instead of re-spending from zero. The human-approval gate routes irreversible tool calls for sign-off over CLI, web, or webhook before they fire, and the LLM cannot bypass it because the gate lives in compiled code, not a prompt. The hosted dashboard is private beta only; teams that need a UI today are self-managing.

Attribute	Declaw	RiskKernel
Pricing	Paid	Free
Free trial	No	No
Open source	No	Yes
Has API	Yes	Yes
Self-hosted option	No	Yes
Platforms	—	Linux, macOS, Windows (Go binary)
Pros	All security primitives — network policy, PII redaction, credential vault, and audit log — share the same execution context inside one SDK, so there are no integration gaps between vendors where an injection or exfiltration can slip through unlogged. Credentials are injected at the egress proxy rather than passed into the VM, which means a compromised agent process cannot read the raw API key even if it tries. L7 domain and SNI filtering with wildcard and regex matching lets you define exactly which external endpoints an agent is allowed to reach, so a prompt injection that tries to POST to an attacker-controlled domain is blocked and audited rather than silently succeeding. Snapshot and pause/resume support lets you freeze idle agents and stop paying for compute mid-task, which matters for long-running workflows where billing otherwise accumulates during wait states. Drop-in compatibility with OpenAI, Anthropic, LangChain, and CrewAI means existing agent code runs inside the sandbox without a rewrite, so the migration cost is measured in configuration rather than refactoring.	Hard per-run dollar and token ceilings enforced in compiled code, which means the kill switch fires before the overspend registers rather than after the invoice cycle closes. Crash-resumable checkpointing, so a process killed mid-run restarts from the last saved state instead of replaying every prior API call and paying for them again. Human-approval gate for side-effecting tool calls that the LLM cannot route around, so irreversible actions — deleting records, sending messages, writing to external systems — wait for a human decision before executing. One-variable proxy adoption with no code rewrite required, so existing agents running against OpenAI or Anthropic get metering and enforcement without refactoring the application. Self-hosted Apache 2.0 binary with BYO provider keys and no telemetry, so teams in regulated or air-gapped environments get full auditability without exporting run data to a third-party service.
Cons	There is no self-hosted deployment option — every agent execution and its outbound traffic passes through Declaw's cloud infrastructure. Teams with data-residency requirements or compliance mandates that prohibit third-party traffic inspection hit this wall immediately; those teams typically end up building a custom Firecracker wrapper with open-source guardrails libraries rather than adopting Declaw. The audit log and guardrail features are only as useful as the policies you define upfront — the docs describe allowlist-based network control, meaning any allowed domain your agent abuses (for example, an attacker using a permitted API as an exfiltration relay) passes through without detection. Teams handling adversarial inputs at scale need to layer additional behavioral monitoring on top, adding back some of the complexity Declaw was meant to eliminate.	The hosted dashboard is private beta only, so teams that need a web UI to monitor, review, or manage runs across agents have no production-ready option yet — they operate through CLI or build their own view against the OpenTelemetry export. SDK adapters are scoped to LangChain, the Claude Agent SDK, and the OpenAI Agents SDK; teams running CrewAI, AutoGen, or any other framework hit the proxy layer only and lose loop-count and tool-level controls until they write their own adapter. The project is maintained by a single developer with no enterprise support tier listed; teams whose compliance posture requires a support contract or SLA will find nothing on offer and will move to a vendor-backed observability or guardrails product instead.

Bottom line

Declaw is paid while RiskKernel is free; RiskKernel is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Declaw and RiskKernel?

Declaw is Paid, while RiskKernel is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Declaw better than RiskKernel?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.