Nace.AI
Nace.AI builds trustworthy, specialized enterprise AI systems that run business processes end to end. Its products turn company policies, procedures and data into small, explainable models and agents that execute complex work while keeping human experts in control of final validation.
At a Glance
- Enterprise finance, accounting and audit teams
- Internal audit, risk and compliance organizations
- Professional-services firms and expert networks
- Banks, credit unions and lending operations
- +4 more
AI Tools by Nace.AI
(1)
Drex DLM
Decision Model for Typed Questions
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Latest News
Nace.AI launched Drex, a small model that decides instead of writing, and reported that it led the public Decision Index.
Nace.AI published Scaling Laws for Hypernetwork-Based Knowledge Injection and introduced the MegaWikiQA benchmark.
Nace.AI announced a $21.5 million seed round led by Walden Catalyst and a research preview for AI-led enterprise workflows.
Nace.AI emerged from stealth with MetaModel 1 and announced $5 million led by General Catalyst; NAVI was presented as its first product.
Products & Services
Proprietary hypernetwork-based technology that dynamically generates task-specific small-model weights from enterprise policies, procedures and terminology, enabling real-time adaptation and precision without relying on a single general-purpose LLM.
Sovereign enterprise intelligence and agent system for audit, compliance and other long-running workflows. NAVI uses a context graph, evidence-based memory, durable execution, small models, continuous learning and human steering to process full populations and produce traceable work.
A small decision model that takes a state and typed questions and returns a probability for every supplied option in one forward pass, with no generated text to parse. It is available as a hosted API and can run in a VPC, at the edge or on premises.
Open-source Nace.AI decision-language-model release based on NVIDIA Efficient-DLM-8B with a decision adapter and pointer head. It supports typed choice, yes/no and score questions, local Python inference, llama.cpp and Ollama runners, and self-hosted agent integration. The repository source is MIT licensed; checkpoint weights and derivative GGUF files are CC BY-NC 4.0.
Market Position
Nace.AI positions itself against generic, large hosted language models and conventional prompt-engineering/RAG approaches by using smaller specialized models, hypernetwork knowledge injection, enterprise-owned deployments and human validation. NAVI competes in AI-led audit, compliance and professional-workflow automation, while Drex differentiates from generative decision systems such as Jev by returning calibrated probabilities over fixed choices in one pass, without generating prose. Its broader alternatives include enterprise AI platforms and audit/compliance automation vendors.
Leadership
Founders
Dos Baha
Founder and CEO; serial entrepreneur who previously led Goat.AI, with an AI research background and experience associated with Google, Meta, Amazon and the University of Toronto.
Zhanibek Datbayev
Co-founder and CTO; former AI infrastructure lead at Meta (Facebook), with large-scale software-engineering experience.
Sudha Valluru
Co-founder and COO; three-time founder and former enterprise operator with experience at Google, Cisco and Apple.
Executive Team
Dos Baha
Founder and Chief Executive Officer
Serial entrepreneur and AI researcher; previously led Goat.AI and has experience associated with Google, Meta, Amazon and the University of Toronto.
Zhanibek Datbayev
Co-founder and Chief Technology Officer
Former AI infrastructure lead at Meta, focused on large-scale software and AI infrastructure.
Founding Story
Nace.AI began in spring/summer 2024 after its founders repeatedly saw enterprises struggle with generic language models that produced unreliable outputs, misunderstood business context and created compliance and operational risk. Drawing on experience at Google, Meta, Amazon and the University of Toronto, they set out to build trustworthy, task-specific intelligence that adapts to company workflows and improves with use.
Business Model
Revenue Model
Enterprise software and AI services sold through paid subscriptions and/or negotiated enterprise order forms, with managed, self-hosted and hybrid deployment options. The company describes a 90/10 operating model in which software performs roughly 90% of workflow execution and experts provide the final 10% validation; Nace.AI's terms state that subscriptions may be billed monthly or annually and that applicable fees are communicated in the service or order form.
Target Markets
- Enterprise finance, accounting and audit teams
- Internal audit, risk and compliance organizations
- Professional-services firms and expert networks
- Banks, credit unions and lending operations
- Insurance companies
- Healthcare organizations
- Financial audit
- Accounting automation and financial close
- Continuous controls and SOX testing
- Claims review
- KYC remediation
- M&A due diligence
- Intel
- Barton
- Prosper
- Mountain America Credit Union