Building theAI-native Enterprise

From strategy to production, we build enterprise AI agents, data foundations, and the infrastructure required to solve real business problems.

We stand behind every solution we deliver.

Animated AI-native enterprise architecture A purple bubble moves upward only on the connector lines between enterprise systems, a unified data foundation, an enterprise AI workforce, business operations, and business outcomes. Each layer glows as the bubble reaches it. Business Outcomes Revenue Cost Time Business Operations Workflows Decisions Automations Experiences Enterprise AI Agents Specialized Agents Orchestration Tools Guardrails Unified Data Foundation Ingest Organize Govern Activate Enterprise Systems ERP &CRM Data &Analytics IT &Security HR &Finance

Three beliefs behind every build.

They shape how we design, deliver, and measure every solution.

01

Agents fail on data, not models.

Reliable agents start with clean, governed, connected data and the context required to act.

02

We are judged on what runs, not what we recommended.

The proof is a secure production system that people use and the business can own.

03

Every enterprise becomes AI-native through execution, not experimentation.

We move from use case and architecture to deployment, adoption, and measurable business value.

From foundation to value.

We build the data, agents, and controls required to move AI into production.

What we build

Data foundations

Clean, connected, governed data that agents can trust.

  • Build the platform, semantic layer, and pipelines.
  • Connect the enterprise systems you already run.
  • Resolve identities across fragmented data.

Enterprise AI agents

Agents that act across your systems, not just chat.

  • Orchestrate specialized agents and handoffs.
  • Build the tools, APIs, and MCP servers agents need to act.
  • Add evaluations, guardrails, and human review.

Strategy and governance

A clear path from use case to an approved production system.

  • Turn use cases into build plans and architecture.
  • Design governance, model risk, and audit trails.
  • Define ownership, quality, and operating controls.

Built by operators.

Our team has spent two decades building data, analytics, and machine learning systems inside global enterprises. We know what these systems must survive after launch.

Where our team built their craft

  • JPMorgan
  • Deutsche Bank
  • EY
  • Diageo
  • Pearson
  • Pfizer
  • Nielsen
  • Microsoft
  • Informa

Industries we know.

We take on work where we understand how the business actually runs.

Publishing and research

Author and institution data, submission-to-sales analytics, and intelligence products for scholarly publishers.

Author 360Identity graphIntelligence products

Media and marketing

Audience data, subscription and advertising products, and editorial intelligence for B2B media and events.

Audience 360Media intelligenceIntent-based experiences

Financial services

Member and customer intelligence, composable marketing architecture, and compliance-grade data for banks and credit unions.

Member 360Composable martechGovernance

Healthcare

Payer and provider data platforms, and operational workflows built inside real PHI constraints.

Claims dataPHI controlsWorkflow agents

Manufacturing and distribution

One commercial picture across quoting, pricing, inventory, customer, product, and supplier data.

Multi-ERP integrationProduct and customer 360Inventory intelligence

Bring us the problem.

It has to work in production. We will help define it, build it, deploy it, and stand behind it.