Local LLM inference with autonomous cost intelligence, cryptographic audit trails, self-healing failover, and content safety — one backend that replaces five tools, cuts AI spend by 30–70%, and keeps every byte on your hardware.
Most AI stacks ship your prompts to OpenAI, have no idea what it costs until the invoice lands, and have zero audit trail when a regulator asks. That's not acceptable for industries where data sovereignty and compliance aren't optional.
Every OpenAI / Anthropic call sends your data to a third-party server. For legal, medical, adult, or financial data — that's a liability, a compliance issue, and a breach waiting to happen.
You have no idea what an AI operation costs before you run it. No budget enforcement. No client billing. No routing logic that saves money automatically. You're flying blind.
When your LLM provider has downtime, your product goes down with it. No automatic fallback. No circuit breaker. No recovery plan. Your customers notice before you do.
GDPR requires verifiable, immutable audit logs. "We logged it in CloudWatch" doesn't pass. Most AI backends have no cryptographic proof of what ran, when, at what cost, or who authorised it.
BYOS bundles what normally takes 5 separate tools — and adds autonomous intelligence on top.
Real-time cost prediction before every call. Intelligent provider routing picks the cheapest option that meets your quality floor. Budget enforcement prevents surprises. Precise billing allocates every cent to the right client or project.
Inference runs on your hardware via Ollama. Self-healing circuit breaker detects failures and routes to Groq in under 60 seconds — then silently recovers. Per-tenant Redis conversation memory keeps context between requests.
HMAC-SHA256 cryptographic audit logs that cannot be modified after creation. GDPR right to access, deletion, and portability built-in. PII auto-detection and masking. Zero-trust middleware on every route.
These are real operating scenarios. The numbers are conservative estimates based on actual AI pricing and typical usage patterns in each industry.
A creator platform with 10,000 active users needs AI for content moderation, caption generation, and DM assistance — but OpenAI's ToS bans adult content, Stripe flags the account, and every prompt leaks performer data to a cloud server.
With BYOS: local inference runs adult content workflows on your own hardware. Age verification gates all content access. NSFW classification flags violations automatically. No ToS violations. No data exposure. No account bans.
A firm processes 800 contracts/month using AI for risk extraction, clause comparison, and brief drafting. Sending privileged communications to OpenAI creates attorney-client privilege concerns and violates bar guidelines in several states.
With BYOS: all inference runs on the firm's own server. Cryptographic audit logs prove exactly what ran, when, and who authorised it. GDPR right-to-deletion handles client data removal requests in one API call.
An agency runs AI workflows for 8 enterprise clients, each needing separate billing, separate rate limits, and separate data isolation. A single shared OpenAI key means one client can see another's costs — and there's no way to bill accurately.
With BYOS: each client is a workspace with its own API keys, RLS isolation, and cost allocation. Intelligent routing routes to the cheapest provider per workspace. Mark up AI costs 40% and generate client invoices directly from audit logs.
A telehealth startup uses AI for clinical note summarisation, symptom triage, and appointment scheduling. Sending patient symptoms and visit notes to any third-party LLM API — including OpenAI — creates PHI exposure that their compliance officer will not approve.
With BYOS: inference stays on the clinical server. PII auto-detection masks patient identifiers before logging. Data retention policies automatically delete records after the configurable window. No cloud PHI exposure — ever.
A single POST /v1/exec call runs your prompt through local Ollama, injects conversation history, and automatically falls back to Groq if the circuit opens — all transparent to your app.
This isn't a thin API wrapper. Every module listed below is production-implemented, tested, and wired into the platform.
AI cost reduction via intelligent provider routing — tracked and proven against single-provider baselines
Cost prediction accuracy within 5% — every prediction tracked vs actuals and validated
Bytes of your data sent to external servers by default — all inference runs on your own hardware
Self-healing recovery time — circuit detects failure, routes to Groq, and recovers Ollama automatically
Cost allocation precision — Decimal(10,6) — no rounding errors when billing clients at scale
SHA-256 chained audit logs — cryptographically verifiable, immutable, passes SOC2 / GDPR audits
OpenAI-compatible endpoint — existing integrations work with a single base URL change. Node.js and Python SDKs included.
Helicone charges up to $500/mo for AI logging alone. Portkey charges $599/mo for an AI gateway. This replaces both — plus adds a full security suite, compliance engine, and content safety platform.
All plans include a 14-day free trial. Self-hosted on your infrastructure — we never see your data.