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Foundation Models for Arabic AI

Arabic AI,
built from the
ground up.

Bahar is a suite of foundation language models trained natively on Arabic and its dialects, served through a single enterprise API. Build chat, search, and generation in hours, not months.

4 model sizes100K free tokens

Bahar Playground

Live API Request

Streaming

Model

Prompt

اكتب فقرة عن دور البحرين في تبني الذكاء الاصطناعي.

Response

Input

18

Output

142

Latency

612ms

Bahar Medium72 tok/s

From signup to production in four steps.

Bahar is built for developer speed. No procurement cycles, no custom training, no waiting on multilingual vendors to support Arabic.

01

Sign Up

Create a Bahar account at bahar.infiniteware.com, verify your email, and you are in. 100K free tokens are credited the moment you land.

02

Get Your API Key

Generate a project key from the dashboard, scope it to staging or production, and test it in the playground without writing a line of code.

03

Pick a Model

Choose Bahar Mini for low-latency tasks or Bahar Large for the heaviest reasoning. Switch between them by changing one string in your request.

04

Ship to Production

Move from playground to production keys, set rate limits and alerts, fine-tune on your own data when ready, and serve customers in Arabic.

An Arabic-first LLM platform, end to end.

From a 60K Arabic tokenizer through fine-tuning to enterprise deployment, every layer is built for the Arab world.

Trained natively on Arabic

Bahar is not an English model with Arabic bolted on. It is pretrained on one of the largest curated Arabic corpora ever assembled, with a custom 60K-token Arabic tokenizer and zero character fragmentation.

Dialect coverage

GulfLevantineEgyptianMaghrebiMSAClassical

Cloud API or on-premises

Start on the managed API in minutes. Move to a private GCC region or air-gapped on-premises deployment when regulation, residency, or scale demand it.

Cloud API

99.9% uptime SLA, GCC region

On-Premises

Air-gap capable, full sovereignty

Fine-tune in the dashboard

Upload your domain data, pick a base model, and launch a fine-tune job. Bahar handles the GPUs, the eval, and the versioned deploy.

LoRASFTRLHF

Production-grade from day one

Auto-scaling, low-latency GCC routing, granular usage metering, and enterprise SSO. Drop the API into your stack and move on.

Throughput

10k/s

Uptime SLA

99.9%

Inside the platform

See exactly what Bahar ships with.

The playground, the models, fine-tuning, docs, keys, and usage, all in one console. Every screen below is the actual product.

Playground

Test prompts, before you write a single line of code.

The Bahar playground is a full chat and completion sandbox. Pick a model, tune temperature and tokens, switch dialects, and watch responses stream right in the browser.

  • Side-by-side model comparison for the same prompt
  • Temperature, top-p, and max-token sliders with sensible defaults
  • Native right-to-left rendering and copy-paste of Arabic text
  • Export your tuned settings straight to a curl or SDK snippet
Bahar playground with live Arabic prompt and streaming response
Model Lineup

Four models, one API, every workload covered.

Pick the size that fits the job. Bahar Mini for high-throughput classification, Bahar Large for the heaviest reasoning. Switch by changing one string in the request body.

  • Bahar Mini, Small, Medium, and Large covering 1.3B to 70B parameters
  • Up to 32K context window across the lineup
  • Per-model pricing and latency profiles published in the dashboard
  • Identical API surface, so your code never changes when you upgrade
Bahar model lineup dashboard with sizes, parameters, and pricing
Fine-Tuning

Fine-tune Bahar on your own data, without standing up GPUs.

Upload your dataset, pick a base model, and launch a fine-tune job from the dashboard. Bahar handles the orchestration, the eval, and the versioned deployment.

  • LoRA and full SFT supported across all base sizes
  • Live eval metrics and loss curves while training
  • Versioned model IDs so you can roll back in one click
  • Private to your account: your data never trains the public models
Bahar fine-tuning dashboard with dataset, base model, and training run
Documentation

Docs that get you to first response in five minutes.

Every endpoint, every parameter, every error code, with copy-ready snippets in Python, JavaScript, and curl. The docs are versioned and searchable, in Arabic and English.

  • Python, JavaScript, and curl examples for every endpoint
  • Bilingual docs: read in Arabic or English with one click
  • Live API explorer with your own keys, no copy-paste required
  • Cookbook recipes for chat, RAG, summarization, and translation
Bahar developer documentation with bilingual API reference
API Keys

Keys, scopes, and rotations you can actually trust.

Issue separate keys per project and environment, scope them to specific models or rate limits, and rotate them without downtime. Audit logs cover every key event.

  • Project-scoped keys with separate staging and production tiers
  • Per-key rate limits and monthly token budgets
  • Zero-downtime rotation with overlapping validity windows
  • Full audit log of key creation, usage, and revocation
Bahar API key management dashboard with scopes and rotations
Usage & Billing

Every token, accounted for.

A single dashboard for usage by model, by key, by project, and by day. See spend in real time, set alerts before you hit a limit, and export every line for finance.

  • Real-time usage graphs by model, key, and endpoint
  • Budget alerts at 50, 80, and 100 percent of monthly cap
  • Per-request token accounting with input and output split
  • CSV and invoice export ready for finance and procurement
Bahar usage and billing dashboard with token graphs and alerts
In production

From banking floors to citizen portals.

Bahar is in production across regulated industries in the GCC. Same API, same models, deployed on the cloud or on-premises depending on the regulator and the workload.

GCC Bank

Retail Banking Group

A retail bank with two million customers fine-tuned Bahar Medium on its FAQ, policies, and product catalog. The model now powers an Arabic-first chatbot across WhatsApp, web, and mobile, with human handoff for complex cases.

  • Seventy-five percent of customer queries fully automated
  • Native Gulf Arabic understanding with English code-switching
  • Annual operating cost reduced by an estimated two million dollars
Cloud API · Bahar Medium, fine-tuned
Government Service

Smart City Citizen Portal

A GCC municipality serving one million residents deployed Bahar Large on-premises for full data sovereignty. The model powers a multilingual citizen services assistant across the website, app, WhatsApp, and Telegram, all from one private deployment.

  • Eighty percent of citizen interactions handled without an agent
  • All data residency requirements met with on-premises hosting
  • Single model serves four channels with one operations team
On-Premises · Bahar Large, air-gapped

Ready to ship Arabic AI without the multilingual tax?

Get Your API Key

100K free tokens credited on signup. No credit card required.