Engineered for Entropy.

We are building self-hosted compliance infrastructure for a probabilistic world. Join us in defining how regulated AI teams prove what happened.

evidence_collector.rs
rust
use akios_pro::evidence::{Collector, EvidencePolicy};
use akios_pro::signals::{LlmCall, ToolCall};

#[tokio::main]
async fn main() -> Result<(), Error> {
    let collector = Collector::self_hosted()
        .policy(EvidencePolicy::eu_ai_act())
        .retain_locally("90d")
        .export_to_siem("splunk")
        .build()?;

    collector.record(LlmCall::new("customer-support"));
    collector.record(ToolCall::new("crm.lookup"));
    collector.flush().await?;
    
    Ok(())
}

The Engineering Philosophy

We don't believe in "prompt engineering" as a substitute for systems engineering. We build robust, type-safe infrastructure.

Rust & Go Core

Performance is a feature. We write our sidecars and data planes in Rust and Go to ensure millisecond-latency overhead and memory safety at the edge.

Deterministic by Default

We treat non-determinism as a bug. Our replay engine ensures that every agent state can be reconstructed bit-for-bit, regardless of the underlying model.

Kubernetes Native

We do not own workflow execution. RADAR integrates with existing infrastructure and evidence pipelines so operators can review what agents did.

The Stack

Tools of the Trade.

Rust

Evidence Core

Go

Network Proxy

TypeScript

SDK & UI

Python

Model Serving

Kubernetes

Deployment

gRPC

Communication

ClickHouse

Telemetry

NATS

Messaging

Postgres

State

Terraform

IaC

From the Logbook.

Technical deep dives into the challenges of AI compliance evidence, observability, and security.
Read all posts
Architecture

The Case for Local Inference

Why we moved our core reasoning loop from GPT-4 to fine-tuned Llama 3 on-prem.

Performance

Semantic Tracing at 10k TPS

Building a high-throughput telemetry pipeline with ClickHouse and NATS.

Security

Sandboxing Python Interpreters

Using gVisor and Firecracker to safely execute untrusted agent code.

Build with us.

We are looking for systems engineers who want to solve the hardest problems in AI infrastructure.

View Career Opportunities