Mumbai : Mphasis, (BSE: 526299; NSE: MPHASIS), a global AI-led, platform-driven technology solutions provider, believes enterprise CTOs must rethink legacy core architectures as agentic AI adoption accelerates. This perspective is reinforced by HFS Research, which identifies ontology-based enterprise knowledge graphs as a critical foundation for safe and scalable AI. HFS Research notes that while agentic systems can accelerate execution, without an explicit semantic control layer, they risk propagating incorrect intent and scaling flaws embedded in legacy logic.

At the heart of the NeoIPTM platform is Mphasis OntosphereTM, an ontology-based intelligence layer within the broader Mphasis NeoIPTM suite that captures business rules, code paths, documentation, and operational artifacts into a structured, continuously updated knowledge graph. By defining what core enterprise concepts mean within a specific organisational context and how they interrelate, Ontosphere creates a persistent semantic layer that can govern and guide agentic systems safely.

Across financial services, insurance, and public sector organizations, modernization has typically been incremental. Many have adopted cloud infrastructure and digital interfaces while leaving core business logic largely unchanged. As agentic AI systems begin to ingest applications and automate decision flows, this embedded logic becomes mission-critical.

Mphasis cited measurable results from client engagements applying its ontology and knowledge graph framework. In a global insurance ITOps and observability programme, the client achieved:

  • 67% accuracy in major incident prediction;
  • 3-5 hours of early warning capability;
  • A 50% reduction in mean time to detect, acknowledge, and resolve incidents.

“At Mphasis, we see AI as an architectural inflection point, not just a technology overlay. Enterprises are entering an AI era where the core can no longer be treated as untouchable. Layering intelligence on top of fragmented systems only scales complexity. The shift now is to make intelligence part of the architecture itself – and NeoIP is helping in doing so,” said Nitin Rakesh, Chief Executive Officer and Managing Director, Mphasis.

“Our research shows that ontologies and knowledge graphs are increasingly important for enterprises adopting agentic AI. Mphasis’ NeoIP platform reflects these principles, embedding semantic intelligence at the core of enterprise architecture to support continuous modernisation and safer AI deployment. The challenge isn’t the absence of intelligence, rather its fragmentation. Enterprises already have the intelligence embedded in code, workflows, and documents – but what they lack is a system of truth for intelligence. The task is to extract, structure, and make it reusable, so AI can drive transformation without repeating legacy mistakes,” said David Cushman, Executive Research Leader, HFS Research.

As agentic AI matures, enterprises will require far greater architectural discipline. Without embedded intelligence grounded in an enterprise context, AI remains merely artificial. The organizations that succeed will be those that can codify their own institutional meaning and leverage it to enable continuous, secure, and well-governed transformation.

NeoIP is designed to do so to reduce repeated relearning cycles that can consume significant portions of traditional or legacy transformation effort. HFS Research describes this approach as a centralised meaning layer that enables enterprises to build and control AI agents safely, while supporting continuous modernisation rather than episodic transformation.