For more than a decade, Olivier Khatib lived in the trenches of enterprise technology — and what he saw was dysfunction on a global scale. Olivier Khatib A data scientist who graduated from Imperial College London, Khatib spent ten years building AI and automation systems for some of the world’s largest organizations. As founder and CEO of London Data Consulting (LDC), he led large-scale transformation projects for HSBC, AXA, and BNP Paribas. London Data Consulting (LDC) London Data Consulting (LDC) And after seeing hundreds of ERP rollouts from the inside, he reached a harsh conclusion: “The ERP industry is still selling 1990s architecture to a 2025 world,” he says. “Everything is siloed, everything is fragmented, and every company knows it.” Khatib didn’t just observe the problem — he lived it. And he realized the issue wasn’t that companies lacked data, automation, or cloud tools. The problem was structural. Every department was running a different system. Every system spoke a different language. And “integration” had become enterprise code for “expensive chaos.” So he built DATANEO — the platform designed to replace that chaos with a single intelligent core. DATANEO DATANEO From ERP Overload to Enterprise Intelligence From ERP Overload to Enterprise Intelligence Khatib had read thousands of RFPs from mid-market companies — many doing $50 million to $500 million in annual revenue — and they all said the same thing in different ways: “Too many systems. Too little coherence.” “Too many systems. Too little coherence.” Traditional ERP vendors promised “end-to-end integration.” In reality, they delivered a patchwork of modules tied together by consultants, APIs, and wishful thinking. DATANEO takes a different stance: stop duct-taping the past. Build for the architecture we actually live in. stop duct-taping the past. Build for the architecture we actually live in. “The modern enterprise is distributed by nature,” Khatib explains. “It’s modular, data-rich, and connected — but ERPs were never built for that. They’re trying to centralize a world that doesn’t want to be centralized.” DATANEO: The AI-Native Enterprise OS DATANEO: The AI-Native Enterprise OS DATANEO doesn’t just sit on top of your systems — it unifies them. At its core is NeoMind™, an AI-native operating system that connects and understands every function of a business: finance, CRM, HR, logistics, projects, and customer support. NeoMind™ NeoMind™ Unlike traditional ERPs, NeoMind wasn’t built around forms and workflows. It was built around context — the real connective tissue of enterprise intelligence. context Each module — Finance+, CRM+, HR+, Project+, Stock+, and Support+ — acts as an intelligent service that plugs into the same reasoning layer. Finance+ CRM+ HR+ Project+ Stock+ Support+ That means every part of the organization shares one ontology, one memory, and one understanding of what’s happening across the business. “You can still use Salesforce, HubSpot, or Workday if you want,” says Khatib. “But once you connect them through DATANEO, they stop being silos and start acting like one living system.” Instead of static dashboards, executives interact with DATANEO in plain English: Example prompts NeoMind can handle in real time: Example prompts NeoMind can handle in real time: “Combine Salesforce leads and Finance+ data to show our top five customers by revenue growth.”“Summarize overdue invoices and correlate them with slow-paying clients in HubSpot.”“Forecast next quarter’s cash flow and highlight suppliers impacting margins.”“Show team performance trends from Workday and suggest areas to optimize headcount.” “Combine Salesforce leads and Finance+ data to show our top five customers by revenue growth.” “Summarize overdue invoices and correlate them with slow-paying clients in HubSpot.” “Forecast next quarter’s cash flow and highlight suppliers impacting margins.” “Show team performance trends from Workday and suggest areas to optimize headcount.” NeoMind retrieves, reconciles, and interprets live data — producing an answer that’s not just accurate, but explainable. Every output includes reasoning, provenance, and confidence levels. That’s not just integration. That’s enterprise intelligence as infrastructure. enterprise intelligence as infrastructure The Model Context Protocol (MCP): AI with Boundaries The Model Context Protocol (MCP): AI with Boundaries Behind DATANEO’s flexibility is its biggest technical breakthrough — the Model Context Protocol (MCP). Model Context Protocol (MCP) MCP acts as a universal bridge between NeoMind and the systems companies already use. Traditionally, connecting enterprise apps required endless custom connectors and middleware. MCP changes that by standardizing how AI interacts with data and APIs. “It’s plug-and-play for enterprise AI,” Khatib explains. “You can connect new systems in hours, not months — and the model immediately knows how to use them.” Each MCP connection creates a temporary, permissioned context, allowing NeoMind to process information securely — without exposing underlying credentials or data structures. temporary, permissioned context Example prompts leveraging MCP connections: Example prompts leveraging MCP connections: “Ingest HubSpot deal data and Finance+ invoices to calculate pipeline conversion rates.”“Generate a weekly financial summary combining accounting, CRM, and HR metrics.”“Pull the last 30 days of support tickets from Support+ and flag recurring product issues.”“Combine project delivery timelines and employee availability to predict resource bottlenecks.” “Ingest HubSpot deal data and Finance+ invoices to calculate pipeline conversion rates.” “Generate a weekly financial summary combining accounting, CRM, and HR metrics.” “Pull the last 30 days of support tickets from Support+ and flag recurring product issues.” “Combine project delivery timelines and employee availability to predict resource bottlenecks.” For engineers, MCP eliminates the need for brittle middleware. For business teams, it means agility — the freedom to evolve stacks without starting from scratch. The Architecture: Distributed by Design The Architecture: Distributed by Design Under the hood, DATANEO isn’t built like traditional enterprise software. It’s designed as a distributed operating system, designed to keep every part of a company’s digital stack connected, consistent, and intelligent. DATANEO distributed operating system The platform runs on a modern Node.js and TypeScript core, split between two main services: one orchestrating all product modules — Finance, CRM, HR, Automate+, and more — and another running the Model Context Protocol (MCP), which powers NeoMind’s secure AI reasoning layer. modern Node.js and TypeScript core Model Context Protocol (MCP) Data flows through a governed Postgres backbone, updating in real time so NeoMind always operates with live context. When it analyzes, predicts, or plans, it draws from a network of large language models — using OpenAI for deep reasoning, Gemini for planning, and other models for retrieval and summarization — grounding every output in verified business data. governed Postgres backbone network of large language models OpenAI Gemini “We designed DATANEO as a self-healing enterprise OS,” says Khatib. “If one part slows down, the others adapt. Every service understands its context and role.” The result is a platform that’s modular, explainable, and adaptive — combining AI reasoning, data integrity, and automation into a single, coherent architecture. AI reasoning data integrity automation It’s not just distributed computing. It’s distributed intelligence. distributed intelligence The Mid-Market Revolution The Mid-Market Revolution While DATANEO scales to global enterprises, its fastest-growing audience is the mid-market — companies between $50M and $500M in annual revenue. mid-market They’re too complex for lightweight tools, too fast-moving for legacy ERP rollouts. They don’t want 18-month “digital transformations.” They want automation that works next week. automation that works next week Example day-to-day prompts from current pilots: Example day-to-day prompts from current pilots: “Identify regions where logistics costs exceed 15% of revenue.”“List underperforming products and their impact on gross margin.”“Predict next quarter’s headcount needs based on current project loads.”“Summarize client churn signals from CRM+ and forecast retention risk.” “Identify regions where logistics costs exceed 15% of revenue.” “List underperforming products and their impact on gross margin.” “Predict next quarter’s headcount needs based on current project loads.” “Summarize client churn signals from CRM+ and forecast retention risk.” Because DATANEO is delivered as a SaaS platform, deployment is instant — companies can onboard and start running intelligent workflows in minutes. DATANEO is delivered as a SaaS platform instant For more advanced integrations or custom data environments, the API-first architecture and MCP layer enable deep, secure connections across existing systems. API-first architecture and MCP layer In both cases, there’s no setup friction, no consultants, no endless rollout cycles. The platform continuously learns from live operations, surfacing inefficiencies, forecasting risks, and recommending actions before humans even spot the patterns. “We’re not selling transformation projects,” Khatib says. “We’re selling systems that just work.” Repair, Replace — and Reimagine Repair, Replace — and Reimagine Khatib doesn’t see DATANEO as just a replacement for ERPs. He sees it as an evolution of how enterprise systems should think. evolution “ERPs will still exist,” he says. “But they’ll stop pretending to be the brain. DATANEO is the cortex that actually makes the business think.” The company raised its first funding in Europe and is now expanding to New York, targeting finance, logistics, and manufacturing — industries suffocating under legacy infrastructure. Its adoption curve has been steep. Once engineers see how MCP and NeoMind operate in real time, few want to go back to traditional architectures. MCP NeoMind Building for Reality, Not Diagrams Building for Reality, Not Diagrams At its heart, DATANEO reflects Khatib’s pragmatic engineering philosophy: “We don’t build for the perfect architecture diagram. We build for the mess companies actually live in.” He sees modern enterprise AI not as a marketing arms race, but as a systems problem — how to make distributed parts work together intelligently, safely, and transparently. systems problem That’s why DATANEO is built on three simple principles: Synchronization over centralizationTransparency over automationContext over dashboards Synchronization over centralization Synchronization over centralization Transparency over automation Transparency over automation Context over dashboards Context over dashboards The result is a platform that doesn’t just analyze your business — it understands it. After a decade of watching the ERP world promise integration and deliver fragmentation, Olivier Khatib decided to stop waiting for the market to fix itself. He built DATANEO, an AI-native enterprise OS that finally brings coherence to the modern stack — whether that means connecting old systems or replacing them entirely. DATANEO In a world of bloated dashboards and brittle integrations, Khatib isn’t chasing disruption. He’s doing something rarer — repairing what enterprise tech broke. repairing what enterprise tech broke. And in the world of ERPs, that might just be the most revolutionary act of all.

This story contains new, firsthand information uncovered by the writer.

Rebuilding the Enterprise Brain: Olivier Khatib’s AI Plan to Make ERPs Intelligent Again

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