India's AI Research Company

Intelligence
that lives
on your ground.

We build the full stack of enterprise AI — foundation models, memory infrastructure, and on-premise deployment. No cloud dependency. No data leaving your walls.

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Foundation Models On-Premise Deployment Memory Infrastructure Edge AI Qualcomm / Snapdragon Data Sovereignty Model Distillation ONYX Runtime Foundation Models On-Premise Deployment Memory Infrastructure Edge AI Qualcomm / Snapdragon Data Sovereignty Model Distillation ONYX Runtime
01 — Who We Are

Research-first.
Ship-obsessed.

BRAHMAI is building the complete stack of enterprise AI — proprietary foundation models, memory infrastructure, and on-premise deployment — designed for organizations where data sovereignty isn't optional.

We are a small, research-first team. Our work spans model architecture, systems engineering, and the hardware integrations that make local AI viable at scale.

AI should run on your machines, on your terms — not as a service you subscribe to.
02 — What We Build

A complete stack.
Nothing outsourced.

  • 01

    bodh & sens Model Family

    A full family of foundation models — LLMs, embedding, classification, TTS, and research-stage architectures. Built for deployment constraints from day one. Quantization-aware training and distillation pipelines that preserve capability under aggressive compression.

    Models
  • 02

    MemoryOS

    A neuroanatomically-inspired memory layer for AI agents. Persistent, structured, session-aware — enabling real continuity without cloud dependency. Model-agnostic and built to run entirely on your own infrastructure.

    Infrastructure
  • 03

    ONYX Runtime

    Local inference runtime with model and mode switching between on-device inference and custom API endpoints. One interface, full control.

    Runtime
  • 04

    Qualcomm / Snapdragon Integration

    Deep NPU integration for on-device and edge deployments. Enterprise-grade AI at the OEM layer — no server required.

    Hardware
  • 05

    Infrastructure Revival

    We take commodity and legacy hardware written off as obsolete and rebuild them into operational AI inference rigs. Sovereignty at a fraction of the cost.

    Hardware

The future of enterprise AI isn't a better API. It's ownership — of the model, the memory, the infrastructure.

03 — Model Family

The bodh
& sens series.

bodh — Sanskrit for enlightenment / awakening. A family of foundation models built for real-world deployment constraints. Designed to keep capability intact under pressure.

bodh — b family
Model Focus Positioning
bodh-b0 Content, Code, Math Distilled for everyday excellence. Punches well above its size on generic tasks — coding, content, mathematical reasoning.
bodh-b1 Agentic & General Engineered for agentic workloads — planning, tool use, multi-step execution. The enterprise all-rounder.
bodh-b2 Automation, Code, Physics The heavy hitter. Deep automation pipelines, complex instruction following, technically demanding domains. Vision-capable.
bodh — x family
Model Focus Positioning
bodh-x1 Consumer Agents Consumer-facing deployments: support agents, personal assistants, legal Q&A, domain-specific applications.
bodh-x2 Code + General x1 extended with strong code generation. The base for AI developer tools and technical applications. Vision-capable.
sens family
Model Focus Positioning
sens-mini-0 Long-context memory Built around Engram-style memory compression. Retains meaningful context at exceptional token depth.
sens-mini-1 Personal AI Single-owner model with real-time context compression. Persistent, personalized intelligence.

All models available for on-premise licensing. However, we do also offer shared cloud API access.

04 — MemoryOS

Teaching AI how to remember.

Most AI systems treat memory as a flat context window — a list of tokens that gets truncated when too long. No structure. No persistence. No understanding of what matters.

MemoryOS draws from neuroscience — attention, consolidation, spatial context, and working memory are each first-class concerns. The result persists across sessions, scales to enterprise context volumes, and runs entirely on your own infrastructure.

Model-agnostic. Currently under active research. Integrated into our enterprise offering and the foundation of the sens model family.

Not just more memory.
Better memory.
05 — The On-Prem Thesis

Why enterprises are moving AI off the cloud.

01

Data Sovereignty

Your data never leaves your infrastructure. Compliance, competitive sensitivity, and regulatory obligations met by default.

02

Predictable Costs

No per-token bills that scale with usage. Fixed infrastructure costs. Competitive on-prem token economics.

03

No Vendor Lock-In

You own the stack. Model updates, capability changes, and pricing are not at the discretion of a third-party API provider.

04

Air-Gapped Deployments

Full functionality in network-restricted environments — government, defence, regulated finance, healthcare.

06 — Research Focus

Active research directions.

We focus on a small number of high-conviction problems rather than broad surface coverage.

  • —

    Model distillation & quantization

    Preserving capability through aggressive compression.

  • —

    Memory architecture for agents

    Durable, structured, fast-access memory that scales.

  • —

    Coreference & entity resolution

    Lightweight neural pipelines for long-context, multi-turn AI.

  • —

    Edge AI on Snapdragon silicon

    Making on-device AI a real enterprise option, not a demo.

07 — Get In Touch

Built for organizations that cannot compromise.

We work with enterprises, government bodies, and technology companies that require AI without cloud dependency. Sensitive data, regulatory constraints, custom model behavior — that's our conversation.

hello@brahmai.in