Navatar has launched an AI-powered CRM operating model on Salesforce, aimed at alternative asset management.
At the center is what Navatar calls a single AI Deal Engine, which is designed to run continuously across the entire investment lifecycle, from sourcing to fundraising, without relying on constant manual data entry. The firm is targeting private equity, private credit, real assets, infrastructure, real estate, and secondaries managers.
Alternative asset managers have spent years customizing their CRM systems to track relationships, deals and investors, only to find themselves still buried in spreadsheets, emails and manual updates. Navatar anticipates that the next evolution of CRM in private markets looks less like a database and more like an operating model.
How AI-Powered CRM Operating Models Can Reshape Dealmaking
CRM has long been positioned as the system of record for client and deal data. But across financial services, and private markets especially, that promise has been hard to realize. Data is fragmented across teams, strategies, and tools, and CRM adoption often drops once deal activity heats up.
Recent research from McKinsey shows that managers in private markets firms still
“work within siloed data environments with no comprehensive, fit-for-purpose, front-to-back platform, making it difficult to integrate diverse data sources.”
Getting the most value out of AI will require coherent, end-to-end operating models instead of patchworks of individual tools, the report added.
Navatar’s approach aligns with a broader shift underway in CRM, as businesses move from static record-keeping to systems that actively deliver insights and next steps.
Recent research from McKinsey & Company notes that many private markets firms are still “working within siloed data and operating environments,” and argues that AI only delivers real value when it’s embedded in coherent, end-to-end operating models rather than bolted onto individual tools.
AI Deal Engine is designed to capture intelligence as it’s created, whether in meetings, emails, deal reviews, or portfolio discussions. It maintains institutional context and aims to advance work automatically across sourcing, diligence, execution, portfolio management, and investor engagement, without relying on manual CRM updates or spreadsheets.
Unlike generic AI assistants, the model is built around the specific realities of alternative asset strategies:
Private equity and growth equity teams get earlier visibility into relevant opportunities, with AI linking new situations to investment theses and past deals.
Private credit teams can unify borrower, sponsor, intermediary, and market data, while AI benchmarks structures and flags emerging risks.
Real estate and infrastructure investors see asset-, tenant-, and capital-partner intelligence in one place to support acquisitions, developments, and refinancings.
Real assets and natural resources teams can connect technical and operational data with relationship and deal context to evaluate risk.
Secondaries and funds of funds gain institutional memory across intermediaries, GP relationships, fund exposures, and LP portfolios.
The goal is a shared operating backbone that works for multi-strategy platforms as well as focused managers, without forcing teams into a one-size-fits-all workflow.
Navatar is also pushing CRM deeper into fundraising and investor relations. Its AI interprets investor engagement across meetings, emails, events, and digital channels, then links that activity back to deals and portfolios.
Fundraising, co-investments, and continuation vehicles can be managed with a tighter feedback loop between investment activity and LP engagement—across flagship funds, private credit and real asset vehicles, and wealth-focused products.
That matters as LPs demand more transparency and faster, more tailored communication, even as managers juggle more vehicles and channels than ever before.
Trust and Control Remain Key as AI Enters Private Market CRM
As AI becomes more embedded in CRM workflows, questions around data security and governance loom large, especially in private markets.
Navatar said its AI operating model is designed to keep client data within secure environments, without exposing it to public AI models where it can be used for training, and to provide guardrails around accuracy, completeness, and traceability when AI is used in decision-critical processes.
In financial services and beyond, CRM platforms are becoming the intelligence layer that connects customer, deal, and operational data in real time. In complex, relationship-driven businesses like private markets, the differentiator is who can act on the vast amounts of data they collect fastest, without adding friction for customers or employees.
