The Ultimate AI Command Center.
Stop overpaying for locked-in Foundation Models. Aeion AI is a unified, multi-provider gateway routing requests across 57 AI providers spanning 9 modality buckets — text, image, audio, video, 3D, embeddings, voice cloning, STT/TTS — with intelligent cost/speed/quality routing, automatic usage tracking, per-tenant cost caps, and zero platform markup. Switching from GPT-4o to dynamically-routed Gemini Flash + DeepSeek for bulk tasks can cut your daily AI spend 99.5%.
Total Intelligence Sovereignty
Intelligent Multi-Routing
Stop hardcoding API keys. The router evaluates each request and routes to the optimal provider based on your strategy (Static / Priority / Cost-Optimized / Intelligent). One call hits OpenAI, the next DeepSeek, the next Groq — your code never changes.
Astounding Cost Reductions
Switching from GPT-4o to dynamically-routed Gemini Flash + DeepSeek for bulk background tasks can cut your daily AI spend by up to 99.5%, saving thousands per month on translation, summarization, and embeddings.
Model Auto-Refresh
A daily cron discovers new models from each provider's `/models` endpoint and registers them within 24h. When OpenAI shipped o4 and DeepSeek shipped R2, no code change or deploy was needed — they appeared in the registry overnight.
Per-Tenant Cost Caps
Tracks every call, aggregates by hour/day/week/month, and enforces hard spend caps per tenant. Warn at 80%, soft-block at 95%, hard-block at 100% — zero billing surprises.
Circuit Breaker Failover
Never experience downtime. If Anthropic rate-limits, the router automatically retries on OpenAI. If OpenAI 5xx's, falls back to Gemini. Latency and error rates feed back into routing decisions in real-time.
Encrypted Credentials
Provider API keys never live in plaintext. They're encrypted at rest with a dedicated, independently-rotatable key, and only admins can read or update them.
Neural Architecture Studio
Beyond calling other people's models — *build your own*. Drag Conv2D / Linear / ReLU / MaxPool nodes onto a canvas and the Universal AST Engine compiles the graph into an idiomatic PyTorch `torch.nn.Module` (forward pass resolved depth-first, with automatic cuda / mps / cpu device detection) — ready to train on your own private data. AI sovereignty, not just API access.
What Ships in Aeion AI
Provider Gateway
Any module in Aeion OS calls AI through one registry — 57 provider adapters wired in, the model catalog refreshed daily, every call tracked automatically. Add a provider once and every module gets it, instead of re-integrating per feature.
Usage Tracking
See spend the way finance actually thinks about it — aggregated by hour, day, week, or month, per tenant — with billing reports ready to hand off and bulk CSV/JSON import for reconciling historical usage from a prior system.
Provider Configuration
Credentials for all 57 providers live encrypted, never in plaintext, with base-URL overrides for custom endpoints and organization/group IDs for multi-org setups like OpenAI and MiniMax — so enterprise account structures aren't an afterthought.
Built-in Model Definitions
100+ models ship with current, pre-loaded pricing — GPT-4o at $5/$15 per 1M tokens, Claude 3.7 Sonnet at $3/$15, Gemini 2.0 Flash at $0.10/$0.40, DeepSeek R1 at $0.55/$2.19 — so cost estimates are accurate the moment you flip a model on, not after a billing surprise.
`ai_dashboards` + `ai_usage_logs` collections
Build custom dashboards by cost, usage, provider, or user, backed by an immutable per-call audit trail — token counts, latency, tool calls, trace IDs — so a "why did this cost so much" question or an auditor's request is a lookup, not an investigation.
57 Providers Across 9 Modality Buckets
One API, every modality, all 57 providers. No vendor lock-in, no proprietary SDK to learn.
Per-Modality Cost Calculators
Aeion AI ships dedicated cost-calculation paths per modality — each routes to the right pricing model so caps and dashboards stay accurate regardless of unit (tokens vs. seconds vs. characters vs. images).
```typescript // Text — input + output tokens calculateTextCost(providerId, model, promptTokens, completionTokens); // → input: promptTokens × pricing.inputPer1M / 1_000_000 // → output: completionTokens × pricing.outputPer1M / 1_000_000
// Image — flat per-image (sometimes per-resolution) calculateImageCost(providerId, model, imageCount, resolution?); // → DALL-E 3 1024×1024: $0.040/image // → Stability SD 3.5: $0.065/image // → Fal: varies by model
// Media (audio / video) — per-second or per-character calculateMediaCost(providerId, model, durationSeconds, characterCount?); // → ElevenLabs TTS: $0.30/1K characters // → Deepgram STT: $0.0043/audio-second // → Runway Gen-3: $0.05/video-second
// Embeddings — input tokens × per-1M-tokens rate calculateEmbeddingCost(providerId, model, tokenCount); // → Voyage voyage-2: $0.10/1M tokens // → Cohere embed v3: $0.10/1M tokens (input) + $0.10/1M (output for reranking) ```
Every usage record stores the modality plus the inputs used to compute cost, so per-modality dashboards (Image Spend, Audio Spend, Video Spend, Embedding Spend) work without re-parsing logs. Spend caps can be set per-modality — e.g. "$50/day on image, $500/day on text" — which is the right granularity for most teams since pricing curves vary so much across modalities.
Every Call Tracked, Every Dollar Accounted
Tracking is automatic and requires no setup — every AI call is logged with full context: tokens, cost breakdown by input/output/media, latency, time-to-first-token, tool calls, and a trace ID for correlation.
Model Auto-Refresh — New Models Within 24h, No Deploy
A daily job checks each provider's model catalog and adds newly-discovered models to the registry. Zero code changes, zero deploys, zero waiting for the next platform release.
The Power of the Neural Bus
Commerce
AI Intent Scoring for abandoned carts, product description generation, churn prediction.
Content
Automated SEO metadata generation, tone rewriting, multi-language translation, image alt-text.
Spatial / Motion Studio
Procedural generation of 3D meshes (Tripo3D, Meshy), PBR materials, interactive scenes, lip-sync visemes (ARKit-52).
CRM
Automated ticket routing, sentiment analysis, intelligent summarization of customer histories, deal-stage prediction.
Cut / Media
Speech-to-text transcription, content moderation, automatic chapter markers, voice cloning for narration.
Inbox / Communications
Smart-reply drafts, intent classification, sentiment-based priority routing.
CTO / AI-buyer questions
LangChain is a framework, OpenRouter is a hosted SaaS router, LiteLLM is a Python proxy. Aeion AI is a *native platform capability* — same database, same audit log, same auth as everything else. The router runs inside the platform itself, not as an external dependency. No latency hop, no third-party data residency, no per-call fee. We use OpenRouter as one of many *upstream* providers, not as our router.
Zero. Aeion AI itself is included free with any module — it carries no separate price and no tier of its own. The actual AI calls cost you exactly what each provider charges — no per-token uplift, no percentage on spend, no minimum commitment.
Yes, on every module — no upsell required. Custom provider adapters let you plug in Ollama (local), vLLM, HuggingFace TGI, or any OpenAI-compatible endpoint. Air-gapped deployments use the Pocket TTS pattern — `baseUrl: "http://localhost:8001"` in the provider config.
Before every AI call, the platform checks current period spend against the tenant's cap. 80% → soft warning to admin. 95% → user warned but call allowed. 100% → call rejected with a budget-exceeded error. The estimate uses the model's built-in pricing and the token count of the prompt.
The daily cron polls each provider's `/models` endpoint and registers new models within 24h. When o4 launched, it was usable in production the next morning — no deploy. Every tenant gets the daily refresh; an on-demand refresh via admin UI or MCP tool is also available.
Yes. Every call writes an audit entry with provider, model, tokens, cost, latency, tool calls, trace ID, and status. Entries are append-only — nothing can be edited or deleted after the fact. Meets SOC 2 CC6.1 (logical access), HIPAA 164.312(b) (audit controls), and ISO 27001 A.12.4 (logging). SIEM export (Splunk, Datadog, Elastic) is available on request.
Circuit-breaker pattern. Each provider has a health score updated continuously from success rate + latency. When OpenAI starts 5xx-ing or rate-limiting, the router auto-routes new requests to the next-best provider matching the strategy. The unhealthy provider gets a backoff timer; recovery is automatic when health restores.
Yes — the AI Spend dashboard shows current period spend per provider, per model, per modality, per user, per tenant (super-admin only). Top consumers, top error codes, top-cost tool calls. Plus 30-day trend graph and per-tenant drill-down.
Aeion AI — Deep Dives
[Pricing](/platform/ai/pricing)
Included free with any module, no tiers — no per-token markup, pay providers directly.
[Architecture](/platform/ai/architecture)
One engine, 57 provider adapters, 5 routing strategies, fallback chains, end-to-end request flow.
[Security](/platform/ai/security)
Credential locality (your provider keys live in your tenant's isolated data, never a third party), full usage-log audit, per-tenant isolation, SOC 2 + HIPAA + GDPR + FedRAMP mapping.
[Providers Catalog](/platform/ai/providers-catalog)
All 57 providers across 9 modalities — LLM / image / voice / video / 3D / embeddings / rerank.
[Tech Specs](/platform/ai/tech-specs)
Module inventory + system metrics.
Compare vs AI Gateways
[vs Enterprise AI Platforms](/platform/ai/competitive/vs-enterprise-ai)
BYOM beats vendor lock-in.
[vs Vercel AI SDK / LangChain](/platform/ai/competitive/vs-vercel-langchain)
Backend-first vs library-first AI tooling.
[vs Portkey](/platform/ai/competitive/vs-portkey)
Native, zero-markup multi-provider gateway vs hosted gateway with per-request markup.
Provider Integration Walkthroughs
[OpenAI](/platform/ai/integrations/openai)
GPT-4o + o3 + DALL-E + Whisper + embeddings + Azure tenancy.
[Anthropic](/platform/ai/integrations/anthropic)
Claude 4 family + prompt caching for 90% cost reduction + Bedrock / Vertex.
[Google](/platform/ai/integrations/google)
Gemini 2.5 Pro/Flash/Flash-Lite + 2M context + native multimodal + Vertex AI.
[Groq](/platform/ai/integrations/groq)
Sub-100ms LPU silicon for real-time UX.
[Ollama](/platform/ai/integrations/ollama)
On-prem self-hosted LLM (vLLM / TGI / TensorRT-LLM compatible).
[Voyage](/platform/ai/integrations/voyage)
Best-MTEB embeddings + domain-specific variants for RAG.
Use Cases by Workload Shape
[Chatbot Apps](/platform/ai/use-cases/chatbot-app)
Streaming + fallback + cost cap patterns for ChatGPT-style products.
[Content Generation](/platform/ai/use-cases/content-generation)
Image / video / voice / 3D from one API with per-modality cost caps.
[Voice Products](/platform/ai/use-cases/voice-products)
Sub-700ms voice-to-voice with the Deepgram + Groq + Cartesia stack.
[Agentic Workflows](/platform/ai/use-cases/agentic-workflows)
Tool use + iteration caps + per-step provider routing.
[On-Prem AI](/platform/ai/use-cases/on-prem-ai)
Air-gapped deployment for HIPAA / FedRAMP / DoD IL4-IL5 / classified workloads.