Can you prove what your AI agent actually decided? DCL Evaluator gives you cryptographic proof of every LLM decision β deterministic, tamper-evident, bit-for-bit reproducible. Every output is evaluated against your policy. COMMIT or NO_COMMIT. Each decision gets a SHA-256 hash, chained to the previous one. Works with Ollama, Claude, GPT-4, Grok, Gemini. 100% offline. Desktop-first.
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Maker
π
Hi Product Hunt! π I'm Dari, indie developer from Siberia.
I built DCL Evaluator after realizing there's a blind spot in every AI pipeline: you can log what an agent said, but you can't cryptographically prove it. Probabilistic guardrails help, but they're not reproducible β same input, different answer.
DCL is different: deterministic policy engine + SHA-256 hash chain = tamper-evident audit trail that holds up under regulatory scrutiny.
Happy to answer any questions about the architecture or use cases. And yes β it runs fully offline with Ollama. π¦Ύ
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Maker
Curious what's the biggest pain point for you when auditing agent behavior β is it reproducibility, policy compliance, or something else entirely?
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@daririnchΒ The real problem is the lack of provability. You can set up compliance, but how do you prove to a regulator or a client that the agent followed the rules in every single iteration?
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Maker
@shitcoinerΒ Exactly the distinction that matters: compliance is a promise, provability is a receipt.
DCL produces tamper-evident audit logs per decision cycle β TX-hash verified, independently anchored. A regulator doesn't need to trust the agent; they can inspect the trace.
Curious what's the biggest pain point for you when auditing agent behavior β is it reproducibility, policy compliance, or something else entirely?
@daririnchΒ The real problem is the lack of provability. You can set up compliance, but how do you prove to a regulator or a client that the agent followed the rules in every single iteration?
@shitcoinerΒ Exactly the distinction that matters: compliance is a promise, provability is a receipt.
DCL produces tamper-evident audit logs per decision cycle β TX-hash verified, independently anchored. A regulator doesn't need to trust the agent; they can inspect the trace.
That's the core design principle.