I've run the investment process — sourcing, underwriting, IC, asset management, dispositions. I know what the output needs to look like because I've been the one presenting it. This page is the honest version of what AI can and cannot do for the investment function.
Every investment team I talk to has the same story. Someone on the team figured out how to build models faster, pull comps in minutes, automate a few alerts. Those are real wins. But they stay scattered because nobody has connected them into the investment process itself.
The gap between sporadic AI usage and systematic AI infrastructure is where most of the uncaptured value is sitting right now. Closing that gap is what I do — as a practitioner who's built these systems on live transactions, not as a vendor selling software.
Agents monitoring listing platforms, broker networks, and public records around the clock. Properties screened against your specific criteria — return thresholds, geography, asset class, deal size — before anyone on your team sees them. The pipeline fills itself. Your team evaluates instead of hunts.
An offering memorandum, financials, and public data go in. A first-pass underwriting model, comparable transactions, cash flow projections, and a preliminary IC memo come out — in hours, not days. Your analysts spend their time stress-testing assumptions and structuring the deal, not assembling the file.
Diligence checklists tracked automatically. Environmental, title, survey, zoning, and lease abstraction batch-processed and cross-referenced. Lender packages assembled to each lender's specific format. Nothing falls through the cracks at closing because the system watches everything in parallel.
Monthly property performance compiled and formatted automatically. Variance explanations drafted, anomalies flagged. Business plan tracking, lease renewal analysis, and CapEx approval workflows running continuously. Your asset managers focus on leasing strategy and value creation, not spreadsheet assembly.
Quarterly reporting that used to consume your team for two weeks gets drafted in hours. Capital account statements, fund performance narratives, distribution waterfalls — all calculated and formatted to your standards. LP communications and DDQ responses generated from your approved language and data.
Lender covenant tracking, cash management reconciliation, K-1 preparation across dozens of entities — monitored and assembled continuously. Tax prep checklists and depreciation schedules stay current. Your finance team focuses on treasury strategy and lender relationships.
I come in with twenty years of doing the same work your team does every day: acquisitions, underwriting, asset management, capital markets, investor relations. That experience is what makes the technology work, because I understand which parts of the process are ready for automation and which parts need a human being.
We start by sitting down with your team and mapping how work actually flows through your firm. The real version, not the org chart version. Where does senior time get consumed? Where are the bottlenecks slowing your ability to move on a deal? Where is institutional knowledge locked in someone's head or buried in email threads?
From there, we pick two or three workflows where the impact will be obvious and the team will feel it immediately. We get those running, the team sees the difference, and that builds the credibility to go deeper.
Then we build the real infrastructure: autonomous agents trained on your specific criteria and running continuously. Every deal memo, every IC discussion, every market call feeds back into the system. Over time, it starts to reflect your firm's philosophy and risk appetite. That's the moat.
The last twenty percent — the judgment calls, the structural instincts, the pattern recognition that comes from two decades of principal-side investing — that's still a human job. The relationships that get you into a deal. The gut sense that something is off in the numbers. The ability to read a room in an IC discussion.
AI doesn't replace any of that. It gives you back the time and bandwidth to do more of it. That distinction matters, and it's the line I help clients draw correctly.
Owner-operators and PE real estate firms that have strong teams and know this matters, but don't have a dedicated technology function and haven't had the bandwidth to evaluate tools, test vendors, and build systems while also running a portfolio.
Firms where the CEO or CIO recognizes the urgency but needs someone who speaks both languages — the language of deals and the language of systems — to actually build the thing.
The firms that build this layer now will attract better deals, better talent, and better capital. LPs evaluate operational sophistication alongside returns. The infrastructure itself becomes a competitive advantage in capital formation.
Every system below was built on live transactions and operational data across two real estate investment managers — not simulated, not hypothetical. Company names are withheld, but the workflows are in production today.
Agentic system pulls commercial listings across multiple platforms, scores against the firm's investment criteria — return thresholds, geography, asset class, deal size — and delivers a ranked pipeline before the team arrives each morning. Analyst hours redirected from sourcing to evaluation.
From offering memorandum to IC-ready package: financial analysis, comparable transactions, risk flagging, and structured memo — produced in hours, not days. Each completed deal feeds back into the firm's assumption library, compounding the system's judgment over time.
Institutional-grade SOPs, role definitions, compliance policies, and a fully architected knowledge base — built to PERE 100 standards. Operational infrastructure redesigned to support a $1M-per-head revenue target without adding headcount.
PERE-focused investor database built and continuously enriched — firm intelligence, strategy, AUM, leadership, and contact data updated through automated research agents. Targeted outreach sequences drafted to CAN-SPAM and compliance standards. The fundraising pipeline systematized the same way the deal pipeline is.
A senior operator's complete investment framework — deal evaluation criteria, market views, IC decision history, risk taxonomy — captured, structured, and made retrievable by AI. New team members onboard against the full institutional context. The firm's pattern recognition compounds with every quarter it operates.
Every engagement starts with a conversation. The structure below reflects how most firms engage — but the scope is always tailored to your platform, your team, and your growth trajectory. All three tiers cost a fraction of what you'd pay a single full-time analyst — and produce infrastructure that scales across the entire firm.
A focused diagnostic engagement. We score your firm across the ten dimensions of the AI Maturity Index through structured interviews with your team, produce a peer-benchmarked maturity profile, and deliver an implementation-ready blueprint with a prioritized 90-day roadmap. Typically completed in two to three weeks. Most firms start here.
Deliverable: Firm-specific AI Integration Blueprint with peer benchmarking, ROI analysis, and sequenced implementation plan.
A three-to-six month engagement targeting two to four specific workflows identified in the Blueprint. We build, deploy, and train your team on production AI infrastructure — deal sourcing automation, underwriting acceleration, reporting generation, portfolio monitoring, or capital formation systems. The scope is defined by deliverables and milestones, not hours.
Deliverable: Production AI workflows running on your firm's infrastructure with team training and documentation.
An ongoing embedded advisory role for firms that want a senior operator driving AI strategy alongside the CEO and CIO. I attend IC meetings, participate in asset management reviews, and continuously identify and build the next layer of operational infrastructure. This is how the platform compounds — every transaction makes the system smarter.
Structure: Monthly retainer with defined weekly commitment. Typically 12+ months.
25 minutes · No preparation required · We'll assess fit and discuss your firm's priorities
The questions that come up before, during, and after the diagnostic call. Direct answers, in writing, so you can evaluate fit without scheduling anything.
Chirag Hathiramani is the Chief AI Officer for Commercial Real Estate — a fractional, advisory role he provides to mid-market CRE PE firms with $500M to $5B in AUM. He is a 20-year principal-side operator and former Chief Investment Officer (Casoro Group, Aspen Heights, Vornado), with $3B in transactions completed and author of The Platform CEO.
A Chief AI Officer for CRE owns the firm's AI operating model — what gets automated, what stays human, and how the infrastructure compounds. It is an investment role, not a technology role. Unlike a CIO or CTO, the seat exists to translate principal-side judgment into systems the deal team actually uses. Fractional exists because most $500M–$5B firms do not need this role full-time.
You retain one. Chirag works exclusively as a fractional advisor — he is not seeking a full-time role and does not take W-2 employment. Engagements start with a paid diagnostic, scope into a 90-day implementation, and continue as a monthly retainer with a defined weekly commitment. He attends IC, embeds with the investment team, and builds infrastructure. To explore a fit, schedule a 25-minute diagnostic call via /contact.
You probably do if three signals are present: $500M–$5B in AUM with active deployment, scattered AI experimentation already happening across analysts and asset managers, and rising LP scrutiny of operational infrastructure during DDQs. Below $500M the ROI is harder to justify; above $5B the role typically goes in-house. McKinsey estimates $110–180B of value at stake in CRE from generative AI (McKinsey Global Institute), but only firms with operating leverage capture it.
One test: have they underwritten a deal, read a T12, and reviewed a property condition report? If not, they are a software vendor with a real estate vertical, not an advisor. A real CRE AI advisor has sat in IC, signed an investment memo, and presented to LPs. They know which 20% of the process needs human judgment and which 80% is coordination overhead. Operator-not-vendor is the entire test.
Yes. He spent the first decade at Vornado Realty Trust on a $5B mixed-use institutional portfolio, launched the student-housing acquisitions program at Aspen Heights Partners across 91 university markets, and served three years as Chief Investment Officer at Casoro Group where his team completed 18 transactions exceeding $600M. Across those roles he raised $150M in equity, placed $300M of debt, and completed approximately $3B in transactions.
US-based mid-market commercial real estate private equity firms with $500M to $5B in AUM. That includes GP-controlled equity, debt, and development platforms across office, multifamily, retail, industrial, and specialty asset classes. The sweet spot is firms past the founding phase but before they have a dedicated technology or operations function — typically 10 to 75 people on the platform.
A PropTech vendor sells software and is compensated for adoption. An advisor is retained by the firm and is fiduciary to it. The vendor's optimal answer is always "buy more product." The advisor's optimal answer is sometimes "do not buy software — rebuild the workflow." Deloitte's 2024 CRE Outlook shows 76% of firms exploring or implementing AI; almost all of that activity is vendor-led. Operator-led advisory is a separate category.
The engagement is retainer-based and scoped to the firm — not priced off a public rate card. Every engagement begins with a paid diagnostic (typically two to three weeks) that produces an AI Integration Blueprint scored against the ten dimensions of the AI Maturity Index. From there, firms either move to a Workflow Implementation (3–6 months, milestone-defined) or a Fractional CAIO retainer (monthly, 12+ months typical). To request pricing, contact via /contact.
Build the operating platform first; layer AI second. Roughly 60–70% of knowledge work inside a CRE PE firm is coordination overhead — status updates, reforecast cycles, meeting prep, format conversion (McKinsey, State of Organizations 2023). AI is not primarily a content generation tool; it is a coordination-overhead removal machine. The Platform-first approach uses AI to rebuild the operating model so the firm can scale without proportional headcount.
The AIM Index scores a CRE PE firm across ten dimensions — deal sourcing, underwriting, due diligence, asset management, capital formation, IR, finance and compliance, knowledge capture, talent leverage, and data infrastructure. Each dimension has a maturity score from sporadic experimentation to systematic infrastructure. The output is a peer-benchmarked profile and a sequenced 90-day roadmap. The full framework lives at /aim-index.
Because real estate is a coordination-heavy business by structure: every deal touches acquisitions, legal, lender, asset management, IR, accounting, and tax — across multiple entities, time zones, and document formats. Most of an analyst's week is moving information between people who already agree. That is the Coordination Tax. McKinsey research puts knowledge-work coordination overhead at 60–70%. In CRE PE, my observation puts it higher.
Primarily GPs — sponsors, operators, and platform principals. He occasionally takes on engagements with institutional LPs and consultants who are evaluating GP operational infrastructure as part of their underwriting (operational due diligence, ODD). He does not take engagements with software vendors, brokerages, or service providers selling into CRE PE — that creates a conflict with the GP advisory work.
The full body of writing is at /insights — ten essays covering platform architecture, operational leverage, the Coordination Tax, the LP infrastructure narrative, and the boundary between AI capacity and human judgment. The longer-form thesis is The Platform CEO (foreword by Joel Heikenfeld, Managing Director, Northmarq), available at theplatformceo.com.
25 minutes · No preparation required · We'll assess fit and discuss your firm's priorities