25 workflow automations purpose-built on top of PitchBook — no data leaves your system, no parallel tool for your team to learn.
AI standardizes TB data across periods, builds the QoE model, identifies add-backs with source-document evidence, and drafts the data-book — senior analysts focus on judgment calls, not reformatting. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI monitors Datasite transactions in real time for duplicate payments, split invoices, ghost vendors, and round-dollar patterns — flagging anomalies within 24 hours instead of 10 months. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI reconciles each line of the return against source docs in Datasite and the prior year, explains variances over 5%, and produces a review workpaper the senior can sign off on — cutting review time in half. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI drafts personalized status replies from the live matter state in Datasite, surfaces anything the client is blocking, and escalates tax-sensitive questions to a human — response time drops from hours to minutes. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI matches bank and card feeds to Datasite entries, auto-codes recurring transactions with learned rules, and surfaces only the true exceptions to the bookkeeper — close lands 5 days earlier. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI pulls bills from every channel, extracts line items, assigns GL codes using Transaction Advisory patterns, routes approvals, and sends payment files to Datasite — processing cost per invoice drops from $15 to under $2. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI segments the AR aging, drafts personalized dunning emails by stage, logs promises-to-pay in Datasite, and flags accounts that need a human collections call — DSO drops 12–18 days. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI runs the close checklist, prompts owners for missing items, flags JE variances over threshold, and writes the close memo — close window compresses from 10 business days to 4. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI pre-screens deals against the fund's thesis in PitchBook, drafts a one-page summary per target, and pushes the top 10 to partner review — associate time goes to judgment, not triage. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI builds the LP report from live fund data, drafts commentary per portfolio company, and publishes to the LP portal — reporting goes out on day 15, not day 45. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI surveils 100% of communications, flags anything that might violate rules (promises, performance claims, undisclosed gifts), and routes to the CCO — compliance risk drops, supervision cost too. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI ingests each document into PitchBook, classifies it, checks for completeness and consistency, chases missing items, and builds the underwriter-ready package — clear-to-close times drop. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI reads the conditions, identifies what each condition needs, pulls it from PitchBook or chases the borrower, and re-submits the condition clearance — conditions clear in a day, not a week. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI tracks every renewal date in PitchBook, remarkets at 90 days, drafts the client renewal package with options, and books the review call — retention climbs and premiums stay competitive. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI builds the submission from the broker's intake, routes to carrier APIs via PitchBook, and assembles the quote comparison — submission-to-proposal time drops from 5 days to same-day. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI pre-screens deals against the fund's thesis in Affinity, drafts a one-page summary per target, and pushes the top 10 to partner review — associate time goes to judgment, not triage. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI builds the LP report from live fund data, drafts commentary per portfolio company, and publishes to the LP portal — reporting goes out on day 15, not day 45. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI tracks every renewal date in Affinity, remarkets at 90 days, drafts the client renewal package with options, and books the review call — retention climbs and premiums stay competitive. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI builds the submission from the broker's intake, routes to carrier APIs via Affinity, and assembles the quote comparison — submission-to-proposal time drops from 5 days to same-day. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI assembles the closing package in Affinity, validates each doc, chases stale items, and prepares the settlement statement — closings hit the calendar, not the hope list. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI runs sanctions, PEP, and adverse-media checks nightly, scores each client, and queues anything above threshold for analyst review — BSA risk in real time, not annually. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI tracks every RMD across accounts, drafts the distribution instructions, and confirms execution before year-end — zero missed RMDs across the book. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI ingests target company docs into DealCloud, organizes them per standard data-room structure, redacts sensitive content, and drafts the diligence Q&A index — data room ready in days, not weeks. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI qualifies inbound buyers from DealCloud per the seller's profile, sends NDAs, manages CIM access, and surfaces serious buyers to the broker — broker focuses on negotiation, not gatekeeping. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
AI orchestrates vendor schedules across the property portfolio in DealCloud, dispatches based on owner schedule and weather, and tracks completion — properties stay in white-glove condition with less PM time. Purpose-built for teams running PitchBook — uses the native API or agent integration so nothing leaves the system of record.
We build custom AI workflows on top of PitchBook for any repetitive process. Tell us what you'd automate.
