Applied AI Research in Enterprise Intelligence

Building Sustainable Enterprise AI.Designed to Stay Local

Our research is focused on redefining enterprise AI through a hybrid architecture that seamlessly integrates dedicated AI hardware, governed backend intelligence, and a secure, intuitive interface for human-AI collaboration.

Research architecture

Intelligence where
the enterprise controls it.

Our research is advancing a hybrid enterprise AI architecture that separates local model execution, governed intelligence processing, and the user experience into distinct, secure layers. Each deployment architecture is collaboratively validated with research partners to optimize security, performance, scalability, and governance.

01

Enterprise AI Device

Enterprise AI. Powered locally. Governed by you.

We are developing a dedicated enterprise AI device designed to execute language models within the customer's own environment. By bringing AI closer to sensitive data, the platform aims to strengthen privacy, improve governance, reduce latency, and provide organizations with greater control over their AI infrastructure.

Hardware validation
02

Processing Backend

Secure. Governed. Intelligent.

The processing backend acts as the intelligence layer of the platform, orchestrating enterprise data, business applications, permissions, contextual memory, and AI workflows while ensuring governance, security, and regulatory compliance across every interaction.

Architecture in development
03

Enterprise Frontend

Secure. Intuitive. Enterprise ready.

A secure interaction layer designed for seamless collaboration between people and AI, enabling teams to explore knowledge, review insights, and act with confidence through a trusted enterprise experience.

Prototype research

Research note — our direction is enterprise-controlled AI, where organizations retain authority over model execution, data access, and governance. The final deployment model will be determined through ongoing research and architectural validation.

Research pillars

Researching the future of enterprise intelligence.
Designing the architecture, not just the model.

01

Local Model Execution

Enterprise AI. Executed locally. Controlled by you. No strings attached.

Our research is focused on enabling enterprise-grade AI models to run on dedicated, customer-controlled infrastructure within the organization's operating environment. This approach is designed to enhance data sovereignty, strengthen security, and provide organizations with greater control over AI deployment and execution.

02

Governed Orchestration

The intelligence layer for trusted enterprise AI.

We are developing a governed orchestration layer that intelligently coordinates enterprise systems, permission-aware data access, contextual reasoning, and multi-step AI workflows—enabling secure, transparent, and enterprise-ready automation.

03

Enterprise Interaction

We are designing a simple, secure interface that allows people to work with AI naturally while the underlying orchestration and processing remain behind the scenes.

AB
04

Evidence-Led Development

Our research is guided by real-world validation. We work closely with enterprise partners to evaluate performance, privacy, usability, and deployment requirements throughout the development process.

Development Status

Turning research into
enterprise innovation.

Every milestone is guided by engineering, validated through research, and built for practical adoption.

In validation

Device Architecture

Evaluating dedicated AI hardware for enterprise environments, with research focused on model performance, security, scalability, architectural resilience, and enterprise readiness.

In development

Enterprise Intelligence Platform

Building the core platform that securely orchestrates enterprise systems, manages permissions, retrieves organizational knowledge, and enables intelligent business systems.

In prototyping

Enterprise experience

Testing interaction patterns that keep people informed and in control of consequential AI actions.

Research roadmap

From architecture to evidence

research.log
1RESEARCH PHASE 01
2
3Device architecture
4Local model performance
5Security and network boundaries
6Enterprise deployment constraints
Active development
Research team

Built across AI,
systems & enterprise delivery.

A focused team investigating the hardware, intelligence, infrastructure, and experience as one system.

Leadership & Advisory

Research direction supported by industry experience and governance.

Jack Melendy

Founder

Leading the research direction for enterprise-controlled AI systems designed around real operational constraints.

Advisory Board

Supported by an advisory board with 71+ years of combined experience across enterprise industries.

Jack Melendy, Founder

Technology & Data

Hardware-aware engineering, orchestration systems, applied AI, and interaction design.

Thinura

Head of Technology

Engineering the device, platform, and deployment foundations behind the enterprise AI architecture.

Lahiru

Lead Data Scientist / AI Lead

Researching model behavior, evaluation, retrieval, and applied AI for controlled enterprise environments.

Pelumi

Lead Full Stack Developer

Leading the governed backend and enterprise interaction layer across APIs, workflows, and user experience.

Inuka

Web Developer

Prototyping accessible interfaces that keep people informed and in control of AI-assisted actions.

Built by Hariat

Ask Hari is an active Hariat research initiative, combining applied AI with enterprise platform and transformation experience.

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Research partnership

Help shape
enterprise intelligence.

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We are looking for enterprise design partners with meaningful privacy, governance, or deployment constraints. Share the environment and use case you want to investigate with us.