Kite Logik vs LLM Guard
LLM Guard is a prompt and response scanner. Kite Logik is an action governance layer. Different problems, complementary fixes.
What LLM Guard does
LLM Guard ships a library of input and output scanners — prompt-injection detection, PII redaction, toxicity, secrets, code-language constraints, ban lists. You wire it around your LLM call so prompts get sanitised on the way in and responses get filtered on the way out.
Its strength is content classification: "is this string dangerous?". Models and heuristics decide.
What Kite Logik does
Kite Logik intercepts the agent's runtime events: tool calls, agent spawn, delegation, plans, and resource budgets. Each event is evaluated against an OPA/Rego policy. The policy is a deterministic program — not a classifier — so the same input always produces the same allow/deny decision, and that decision is auditable. It's the same policy-as-code pattern used for Kubernetes admission control, applied to AI agent actions.
Its strength is action policy: "is this agent allowed to do this thing, in this context, right now?".
Why the distinction matters
A prompt-injection scanner can flag a malicious instruction inside a fetched web page, but it can't stop an agent from acting on a request that looks completely benign. "Move $500 to account 123" is not a toxic string. It's a tool call. The question isn't whether the text is suspicious — it's whether this agent, in this session, with this user's scope, should be allowed to invoke transfer_funds at all.
That's an action policy question, and it's what Kite Logik exists to answer. The same question applies to MCP tool servers and any other tool transport.
When to use LLM Guard, when to add Kite Logik
- Use LLM Guard for input/output content scanning — PII, secrets, prompt injection patterns.
- Use Kite Logik for tool-call governance, delegation limits, resource budgets, and an audit trail.
- The pipeline: LLM Guard pre-scan → LLM → LLM Guard post-scan → tool call → Kite Logik policy gate → execution.
Both tools are layers in a defence-in-depth approach to governance for AI agents: content scanners on the model boundary, action policy on the tool boundary.
Side-by-side
| Dimension | LLM Guard | Kite Logik |
|---|---|---|
| Decision basis | Classifiers + heuristics on text | Deterministic Rego rules on structured events |
| Reproducibility | Classifier output can drift with model updates | Same policy + same input = same decision, every time |
| Audit answer | "The scanner flagged this string." | "Policy v1.4.2, rule finance.transfer.requires_approval, denied at 2026-04-24T10:14:33Z." |
| Scope | Prompt + response content | Tool calls, spawn, delegation, plans, budgets |
Frequently asked questions
Is LLM Guard a tool-call governance system?
No. LLM Guard is a library of input/output scanners for LLMs — prompt-injection detection, PII redaction, toxicity, secrets, ban lists. It classifies text. Tool-call governance asks a different question: should this agent be allowed to invoke this action right now? That's deterministic policy, not classification.
Can LLM Guard prevent dangerous tool calls?
Indirectly at best. A scanner can flag a malicious instruction inside a fetched web page, but it can't stop the agent from acting on a request that looks completely benign. "Move $500 to account 123" is not a toxic string — it's a tool call. The policy decision belongs at the action layer.
What does Kite Logik add that LLM Guard does not?
Deterministic OPA/Rego policy on every tool call, agent spawn, delegation, plan, and resource budget — plus an immutable per-event audit log keyed to the policy version that decided each action. Kite Logik's decisions are reproducible; classifier outputs can drift with model updates.
Should I use both LLM Guard and Kite Logik?
Yes — they're complementary. LLM Guard handles content scanning on the prompt and response. Kite Logik handles authorisation on the agent's actions. Together they cover both the model boundary and the tool boundary.
Is Kite Logik an LLM Guard alternative?
Only if your governance need is action-layer (tool calls, lifecycle). For prompt-injection scanning and PII redaction, LLM Guard is the better fit. The two layers compose cleanly when you need both.