How to Build a PE AI Stack in 2026

Why does your PE tech stack matter now?

PE firms are under pressure to evaluate more deals, move faster on competitive processes, and deliver operational alpha — all with lean teams. The firms winning today have stopped thinking about individual tools and started thinking about integrated workflows. According to McKinsey, over 60% of PE firms are now using or piloting AI tools. But most are bolting point solutions onto broken workflows. The firms pulling ahead are building a stack where each layer feeds the next.

The five layers of a modern PE stack

A well-built PE stack covers five distinct workflow layers. Each layer has a purpose, and the tools in each layer should be best-in-class for that function. The mistake most firms make is trying to use one tool for everything, or — worse — having five tools that duplicate effort and don't share data.

• Layer 1: Sourcing — Where you find deals
• Layer 2: Market intelligence — Where you research industries and public markets
• Layer 3: Deal management — Where you track pipeline and relationships
• Layer 4: Portfolio monitoring — Where you track what you own
• Layer 5: Intelligence — Where AI automates analysis, builds models, generates reports, and connects every other layer

Layer 1: Sourcing — Grata

Grata is the leading private company intelligence platform for deal sourcing and market mapping. It maintains a proprietary database of private companies searchable by industry, geography, revenue, business model, and growth signals. For PE firms running proactive sourcing strategies, Grata is best-in-class at surfacing companies that match your thesis. It is focused specifically on sourcing — it does not cover diligence, monitoring, or reporting.

• What it does: Private company discovery, market mapping, thesis-based sourcing
• What it doesn't do: Due diligence, financial modeling, portfolio monitoring, LP reporting

Layer 2: Market intelligence — AlphaSense and PitchBook

These are the two dominant research platforms in PE, and they serve different purposes. AlphaSense aggregates earnings transcripts, SEC filings, broker research, news, and expert call transcripts into a searchable platform. It's best for competitive intelligence, industry analysis, and tracking public market signals. PitchBook provides comprehensive private market data — company profiles, fund performance benchmarks, transaction comps, and investor data. Most PE firms use both: AlphaSense for qualitative research and PitchBook for quantitative data.

• AlphaSense: Public market research, earnings, expert transcripts, competitive intelligence
• PitchBook: Private market data, transaction comps, fund benchmarks, company profiles
• Neither handles: Data room analysis, model generation, portfolio monitoring automation

Layer 3: Deal management — DealCloud by Intapp

DealCloud is the deal management and relationship intelligence CRM built for capital markets firms. It tracks deal flow, manages relationships, organizes pipeline data, and provides reporting on deal activity. DealCloud's strength is as the system of record for your deals and relationships. It has recently added AI features for relationship mapping and deal analytics within the CRM context. DealCloud is not an analytical automation platform — it is a CRM.

• What it does: Deal pipeline tracking, relationship intelligence, activity reporting
• What it doesn't do: Document analysis, financial modeling, portfolio monitoring automation

Layer 4: Portfolio monitoring — Where legacy tools fall short

Portfolio monitoring is where most PE stacks break down. The incumbent tools — Chronograph and iLevel — were designed for structured data collection: sending templates to portfolio companies, collecting responses, and aggregating the numbers. The problem is that portfolio companies don't send clean, structured data. They send PDFs, Excel files with inconsistent formatting, scanned documents, and email attachments. Chronograph and iLevel require manual data entry or template compliance to work. When portfolio companies don't comply with your template (and they rarely do), your ops team spends days manually extracting numbers from whatever format the company sent.

• Chronograph: Structured portfolio data collection and reporting. Requires portfolio companies to submit data in specific formats.
• iLevel: Similar structured data collection and aggregation for PE portfolios. Same dependency on formatted inputs.
• The gap: Neither handles unstructured data — PDFs, inconsistent Excel files, scanned documents. Ops teams fill the gap manually.

Layer 5: Intelligence — Emblem

This is the layer that most PE stacks are missing entirely. Emblem is the AI operating system that sits at the center of the stack and automates the analytical work that currently consumes your team's time. It ingests documents in any format — PDFs, Excel, Word, scanned images — and extracts structured data with 100% source-traced accuracy. Emblem scored 100% on the Vectara RAG benchmark because of its context management architecture: a harness that manages what information reaches the model, preserves fidelity across multi-step workflows, and enforces source tracing at every output. This is not a chatbot or a wrapper around foundation models. It is purpose-built orchestration infrastructure for institutional investors.

What the intelligence layer replaces

Emblem doesn't replace your sourcing tool, your CRM, or your data providers. It replaces the manual analytical work between them. Instead of associates spending days reading CIMs, Emblem reads them and extracts financials with source citations. Instead of building Excel models by hand, Emblem generates working models with formulas traced to source assumptions. Instead of ops teams manually extracting data from whatever format portfolio companies send, Emblem ingests it all — PDFs, messy spreadsheets, scanned documents — and normalizes it automatically. Instead of rebuilding LP reports from scratch each quarter, Emblem generates them from the same structured data that powers your dashboards.

• Due diligence: Data room analysis, financial extraction, memo generation — all source-traced
• Financial modeling: Working Excel models with formulas and linked assumptions
• Portfolio monitoring: Automated ingestion and extraction from any document format — no templates required
• LP reporting: Branded reports in PowerPoint, Word, and Excel generated from your live data
• Emblem Listen: Call recording and transcription, auto-tagged to CRM deals
• Email ingestion: Forward emails or read from CRM — documents processed automatically

Why general-purpose AI doesn't solve this

ChatGPT, Claude, and Gemini are powerful reasoning engines but they are not systems. Feeding a 500-page data room into a context window and asking for analysis produces unreliable results because attention degrades at scale. Agentic workflows that chain multiple steps together compress context between steps — by step five, the agent is reasoning over paraphrased summaries, not original data. Emblem solves this with a context management architecture that maintains structured intermediate state across workflow steps instead of compressing everything into natural-language summaries. For the full technical explanation, see our article on why foundation models alone are not enough for institutional investors.

The recommended PE stack

For a mid-market PE firm, the optimal stack is five tools across five layers — each best-in-class for its function, all connected through CRM and cloud storage integrations.

• Sourcing: Grata — private company discovery and market mapping
• Market intelligence: AlphaSense (qualitative research) + PitchBook (private market data)
• Deal management: DealCloud — pipeline tracking and relationship CRM
• Intelligence: Emblem — due diligence, modeling, portfolio monitoring, LP reporting, and the AI layer that connects everything