Exogram vs RiskKernel

Exogram 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.

Exogram

Exogram is an execution governance layer that intercepts AI agent actions — payments, database writes, customer emails, record updates — and applies a policy decision before anything hits your infrastructure. The vendor describes a four-way enforcement decision: allow, deny, escalate, or log. Policy rules are checked at runtime, not after the fact, which means a $25,000 invoice approval blocked against a $1,000 limit never reaches your payment system. The immutable audit trail is positioned for SOC 2, HIPAA, and financial compliance workflows. The tool is not itself an agent runner — it assumes you already have an agent; it governs what that agent is allowed to touch.

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	Exogram	RiskKernel
Pricing	Paid	Free
Free trial	No	No
Open source	No	Yes
Has API	Yes	Yes
Self-hosted option	No	Yes
Platforms	SaaS, Cloud	Linux, macOS, Windows (Go binary)
Released	2025-05	—
Pros	Runtime policy enforcement at the tool-call boundary, so unauthorized payments and database mutations are blocked before they execute rather than flagged after the damage is done. Four-way enforcement decisions — allow, deny, escalate, log — which means regulated workflows get a human review step without building a custom approval queue on top of your agent stack. Immutable audit logs positioned for SOC 2 and HIPAA compliance, so teams in regulated industries have a defensible record of every action an agent attempted and what decision was returned. Pre-built integrations with LangChain, CrewAI, AutoGen, Vercel AI SDK, and LlamaIndex, so teams already running these frameworks add a governance layer without rewriting their agent code. An open protocol spec (EAAP) published as RFC-0001, so teams who need to audit, extend, or independently verify the governance model are not working against a black-box contract.	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	Exogram governs actions but does not orchestrate agents — teams that need branching logic, memory, or coordination between multiple agents still maintain a separate orchestration layer, which means adding Exogram adds a second system to debug when an escalation fires unexpectedly. No self-hosted deployment option is described on the vendor page, which means teams whose compliance requirements mandate on-premises data residency — common in financial services and healthcare — cannot use Exogram without routing agent traffic through external infrastructure; those teams move to building policy enforcement into their own API gateway instead. The tool launched in approximately May 2025, so production case studies at scale are not yet publicly available; teams evaluating for high-volume payment workflows are working from architecture documentation and demos rather than documented incident records from comparable deployments.	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

Exogram 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 Exogram and RiskKernel?

Exogram 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 Exogram 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.