Everything you need to ship — model inference, memory, jobs, data — in one platform, not nine. OpenAI-compatible. Built to run inside the country it's serving.
# Keep your SDK. Change one line. from openai import OpenAI client = OpenAI(base_url="https://api.openai.com/v1") client = OpenAI(base_url="https://infer.manara.ai/v1") response = client.chat.completions.create( model="llama-3.3-70b", messages=[{"role": "user", "content": "..."}], ) # ✓ tokens billed in local currency · ~30ms p50 · stays in-country
Everything an AI application needs, on the same backend. Inference is the headline. The other five are what stops you from re-inventing the backend on a Tuesday.
Managed vLLM endpoints. Drop-in replacement for the OpenAI SDK — chat, embeddings, function calling, streaming, batch. Pay per token, billed in local currency.
Managed pgvector with hybrid search and reranking. Embeddings co-located with inference — your retrieval, rerank, and model call hit the same region. Single-digit-millisecond internal latency. Pure Postgres underneath, so vectors and business data live in one SQL query.
Long-running tasks, schedules, retries, dead-letter queues. Typed step functions that resume after failure.
Branching, PITR, read replicas, scale-to-zero. Object storage with in-region durability. The boring parts, done right.
Route across local and frontier models. Per-team spend caps. Semantic caching. Fallback chains. Content policy at the gateway, not in your app.
The governance layer regulated buyers can't ship without — built into the same platform as your inference and vector. Three capabilities, one boundary, everything stays in-country.
Manara is one platform with one control plane, one billing engine, and one boundary across every region we run in. A request from your app touches inference, vector, and Postgres without leaving the same datacenter — let alone the same country.
The teams onboarding to Manara today are building production AI features that don't fit a hyperscaler. Each of these is a real shape of customer; none of them is a fit for "just call OpenAI."
Frontier inference APIs are fast to ship on but slow to defend in front of a compliance review. Hyperscaler regions are defensible but expensive, slow to set up, and missing the AI layer entirely. DIY on Kubernetes is technically possible and a year of your life. Here's how Manara compares.
Two audiences buy at the top end: regulated enterprises who need the platform delivered into their compliance perimeter, and operators who want to run it under their own brand. We've designed for both.
For banks, telcos, healthcare, and government. Manara deployed inside your network with optional air-gap mode. Source escrow. SOC2 + PDPL ready. Your auditor signs once; your engineers stop praying.
Talk to enterprise →For carriers, datacenter operators, and national clouds. Federate with the network, white-label the experience, monetize the infrastructure you already own. Three program tiers, partnership applications open.
See the partner program →Free tier on every account. Per-token inference, per-second compute, per-GB storage. Billed in your local currency. No "contact sales for pricing" theatre.
For prototypes, internal tools, and the first weekend of a real product.
Per-token inference. Per-second compute and Postgres. Per-GB vector and storage.
Committed-use discounts, sovereign control plane, dedicated support, custom SLAs.
base_url and the migration is done.base_url change). They add vector when they build RAG, queues when they ship agents, governance when their compliance officer asks. Use what you need; the rest costs nothing until you turn it on.$50 free credit. No card. Llama, Qwen, Jais, DeepSeek — running where your users are, billed in your currency, governed by their laws.