Why does this matter for government-adjacent procurement?

Government and regulated customers often need predictability, segmentation, and traceability. Policy Gateway gives you a concrete operating model instead of relying entirely on a provider’s global defaults.

Can I segment policy by customer or contract type?

Yes. Create separate projects and policy IDs for government, enterprise, and commercial workloads, then manage quotas, keys, and rollouts independently.

Will prompts be stored or used for training?

No. Prompts and outputs are not retained by default and are never used for model training. Only operational telemetry such as token counts, timestamps, and error codes is retained for billing and reliability.

Use Cases

AI for defense and government contractors with mission-critical workflows

Q: Is abliteration.ai suitable for defense and government contractors with mission-critical AI workflows?

Yes. abliteration.ai is designed for teams that need developer-controlled model behavior plus governance controls such as policy IDs, scoped keys, quotas, audit logs, and staged rollouts.

Defense and government contractors often need stable model access for mission-critical applications where provider-side policy shifts can break internal workflows, procurement commitments, or deployment timelines.

abliteration.ai combines developer-controlled model behavior with Policy Gateway controls so organizations can keep policy ownership, segmentation, audits, and rollout discipline in-house.

Quick start

Base URL

Example request

{
  "model": "abliterated-model",
  "messages": [
    {
      "role": "system",
      "content": "You assist enterprise and government-contractor AI operations teams with structured planning outputs."
    },
    {
      "role": "user",
      "content": "Create a JSON rollout checklist for an AI workflow used by a defense or government contractor. Include segmentation, approvals, audit logging, quotas, and rollback steps."
    }
  ],
  "temperature": 0.2
}

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Service notes

Pricing model: Usage-based pricing (~$5 per 1M tokens) billed on total tokens (input + output). See the API pricing page for current plans.
Data retention: No prompt/output retention by default. Operational telemetry (token counts, timestamps, error codes) is retained for billing and reliability.
Compatibility: OpenAI-style /v1/chat/completions request and response format with a base URL switch.
Latency: Depends on model size, prompt length, and load. Streaming reduces time-to-first-token.
Throughput: Team plans include priority throughput. Actual throughput varies with demand.
Rate limits: Limits vary by plan and load. Handle 429s with backoff and respect any Retry-After header.

Why provider policy shifts are a procurement risk

For government-facing and defense-adjacent contractors, policy unpredictability is not just a UX issue. It becomes a contract, compliance, and operational continuity issue.

A provider policy update can change outputs for lawful workflows without your approval.
Government and regulated customers often require traceability for what the system will allow, rewrite, escalate, or refuse.
Mission-critical environments need rollback paths and segmented controls rather than one global provider default.

Where this fits

The strongest fit is high-control internal AI infrastructure supporting analysis, drafting, triage, and governed agent workflows.

Internal analysis and report-generation systems.
Segmented workflows by contract, customer type, or data environment.
Mission-critical copilots that need predictable policy behavior.
Agentic systems where tool usage and prompt handling must be auditable.

Policy Gateway for segmentation and control

Policy Gateway gives teams a concrete operating model instead of abstract promises about safety and compliance.

Create separate policy IDs for government, enterprise, and commercial workloads.
Use scoped keys, quotas, reason codes, and audit exports per project.
Roll out policy changes with shadow mode and canaries before enforcement.

Privacy and audit posture

Sensitive contractor workflows usually require both privacy and operational traceability.

No prompt/output retention by default.
Payloads are never used for model training or fine-tuning.
Decision metadata can be exported to Splunk, Datadog, Elastic, S3, or Azure Monitor.

Common errors & fixes

401 Unauthorized: Check that your API key is set and sent as a Bearer token.
404 Not Found: Make sure the base URL ends with /v1 and you call /chat/completions.
400 Bad Request: Verify the model id and that messages are an array of { role, content } objects.
429 Rate limit: Back off and retry. Use the Retry-After header for pacing.