AI EncryptionOptimization Agent
Strong encryption without the latency tax. Dynamically tunes cipher mode, key size, and chunk size to your workload.
AKRUM's AI Encryption Optimization Agent is one of five prebuilt guardrails. Turn it on to select encryption settings for each workload on every agent action, with no rules to write. AI may assist with interpretation and orchestration, but the deterministic policy engine owns every ALLOW, DENY, or CHALLENGE decision.
Overview
What this AI Agent does
For each workload, deterministically selects the cipher, key size, and chunk size that meet your security tier while hitting your latency and throughput targets, from a published cost model, not guesswork. The same inputs always yield the same result.
Acts as a guardrail on encryption configuration: it returns an ALLOW, DENY, or CHALLENGE decision: allow when a configuration meets your security tier and performance target, challenge when it’s compliant but misses the target (with the change to make), and deny when it falls below the required strength (for example, a sub-256-bit key or a non-FIPS cipher on a government tier). The deterministic engine owns the verdict, not an AI model.
Enforced inline through the Guardrails SDK: allow proceeds, deny is blocked, challenge surfaces the recommended settings, and every decision is signed with post-quantum ML-DSA and written to a tamper-evident log.
How it works
A four-step guardrail flow
Send the workload
Your agent or app sends the workload profile (type, payload size, device class, throughput target, security tier).
Evaluate the options
The deterministic engine scores candidate cipher, key, and chunk settings against a published throughput-and-security cost model. The AI never makes the decision.
Return a decision
It returns ALLOW, DENY, or CHALLENGE with the recommended cipher, key size, and chunk size and their latency/throughput estimates.
Enforce inline
Allow proceeds with the configuration, deny blocks settings below your security tier, challenge surfaces the change to make, and the signed decision is logged, tamper-evident.
Sandbox
Try it live
Adjust workload parameters and run the same deterministic recommendation engine the API runs.
{ "recommended": { "cipher": "AES-256-GCM", "chunk_size_bytes": 16384, "key_size_bits": 256, "estimated_latency_ms_p50": 4.2, "estimated_throughput_mbps": 850, "rationale": "Balanced default: AES-256-GCM with 16 KB chunks on AES-NI-enabled servers." }, "alternatives": [ { "cipher": "AES-128-GCM", "chunk_size_bytes": 16384, "key_size_bits": 128, "estimated_latency_ms_p50": 3.1, "estimated_throughput_mbps": 980, "rationale": "30% lower latency when 128-bit security is sufficient." }, { "cipher": "ChaCha20-Poly1305", "chunk_size_bytes": 32768, "key_size_bits": 256, "estimated_latency_ms_p50": 4.8, "estimated_throughput_mbps": 760, "rationale": "Non-AES-NI fallback with competitive throughput." } ], "evaluated_at": "2026-01-15T10:00:00.000Z" }
Simulated response: no real inference is performed.
Data sources
Benchmarked against open performance data
- Published cipher performance characteristics (OpenSSL speed, libsodium docs) encoded as per-device-class throughput tables in the engine
- NIST SP 800-38D (GCM mode) and RFC 8439 (ChaCha20-Poly1305) for mode selection rules
- Hardware acceleration availability per device class (AES-NI, ARM Cryptography Extension)
- Planned, not yet connected: live benchmark ingestion from your own AKRUM Benchmark runs
All sources are public and updated as new chip releases and library versions ship.
Built for media & streaming
Protect high-value content from script to stream.
In media, one pre-release leak can cost a release. And protection has to travel with each asset through production, storage, and delivery without ever slowing real-time streaming. The Encryption Optimization Agent automatically tunes cipher, chunk size, and key settings for your workload, so protection follows the content and never becomes the bottleneck.
Data it protects
- Films
- TV episodes
- Scripts
- VFX and animation assets
- Marketing materials
- Production archives
Compliance alignment
What does "dynamic cipher tuning" actually do?
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It picks cipher, chunk size, and entropy source for each stream based on workload profile and observed performance. Instead of one static configuration, the agent adapts to the codec, bitrate, and latency target you actually care about.
How does it keep latency low for real-time and streaming workloads?
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By sizing chunks to the codec's natural frame boundary, pre-warming entropy buffers, and choosing GCM modes that pipeline well on the host CPU. The result is consistent encryption overhead well within real-time and live streaming budgets.
Does optimizing for speed reduce security?
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No. The agent only chooses between configurations that meet AKRUM's security floor: AES-GCM family, keys derived from the Cellular Automata entropy engine mixed with the OS CSPRNG, modern TLS. Optimization happens inside that safe envelope, so you trade off implementation cost, not cryptographic strength.
Which streaming protocols and workloads are supported?
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HLS, DASH, WebRTC media flows, low-latency live streams, and high-throughput batch pipelines that look like streams to the network. Anything that ingests chunked data over TLS can be tuned by the agent through its REST endpoint.
Is there a free sandbox to test it?
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Yes. The sandbox lets you describe a workload, codec, bitrate, latency target, and see the agent's recommended cipher, chunk size, and entropy source plus the expected overhead. Free covers exploration before you ship a production key.
Ready to integrate?
Get an API key and start calling AI Encryption Optimization Agent in minutes.