IP Lifecycle Management in the AI Era

Large design enterprises have multiple concurrent activities around IP of various types: software/firmware, blocks defined in RTL or HLS, verification IPs of multiple different types, physical implementations, scripts/files for timing, power management, etc., etc. Each of these continues to evolve and branch to serve different product design needs and must be tracked against appropriate metrics, known problems, and performance in production if available. So far, a well-known need supported by IP Lifecycle Management (IPLM) systems from companies like Perforce. What changes with AI? Agentic flows are proliferating widely in design, offering many advantages but also creating a hidden problem. Such systems explore more options (that’s the point) and teams evolve their own variant workflows. More data, more variants, now data is proliferating explosively. When you want to get insight into the best IP branch and rev for your purposes, across products, teams and geographies, how can you navigate through this tangle of possibilities?

Data traceability in heterogenous design ecosystems

From a local design team perspective, it might seem that this need is already handled by whatever flavor of data management system they subscribe to. Sadly, that is no longer sufficient to handle modern design ecosystem complexities. Requirements might be defined in multiple possible formats (Perforce, Doors, Jama, Excel, etc), data management can be equally heterogenous across domains and teams (ClearCase, Git, Subversion, etc) and design tools and support are equally diverse (Jenkins, Cadence, Siemens, Synopsys, in-house formats). EDA providers offer their own powerful AI databases, but these are naturally designed to work best within their own ecosystems, not across multi-vendor environments.

This raises the obvious question of how best to search across such a diverse span of data for parametrics, status, history, ownership, contacts, while recognizing that each object may have many variants (continuing to evolve), sourced from and/or used in multiple product teams and sites around the globe. Trying to mirror detailed design and analysis data in giant data lakes would be wildly impractical. A better approach is a system which can track metadata with pointers to source data where needed for a deeper dive, guided by natural language search and exploration. To not only find a best fit to immediate needs but also to trace where, how that option was developed and what KPSes to watch out for.

It seems improbable that such a truly general system from commercial hardware or software design systems vendors could gain traction for the obvious reasons. Better would be a platform developed outside that ecosystem, with hooks to support metadata updates for all objects in a development flow, as they become available. Perhaps at some point this might evolve into an open-source standard, but the AI data explosion forbids waiting for an ideal solution. Perforce has stepped up with an effective solution, usable and actively in use today.

Perforce IPLM with MCP and RAG Server

The latest version of the Perforce Helix Core, now called Perforce P4, is designed and AI-enabled to manage this task in heterogenous and agentic supported systems in large design enterprises. They have a nice quick elevator-pitch on their webpage:

Git was built for a single maintainer. Perforce P4 was built for the shape of work agentic development takes: many contributors working in parallel across a mix of code and large binary assets.

Tools can update status through an API. Vishal Moondhra (VP of Solutions at Perforce) tells me that customers have already developed their own in-house hooks to the platform, as have Siemens, and that Perforce are working with other design ecosystem vendors to establish similar support.

This capability isn’t just for (human) search and exploration. Perforce have now rolled out P4 MCP, allowing AI agents to access version control history, data, and code reviews (within allowed permissions). You can build IPLM intelligence right into your own agentic workflows.

Exciting stuff. Perforce with be at DAC 2026 in Long Beach – check it out!