SOLUTIONS · PROFESSIONAL SERVICES
Professional services
AI for professional services firms works when it can read the systems the firm already runs: the CRM (often DealCloud), SharePoint, Outlook and the billing system (often BillQuick). OutcomeCatalyst connects those systems into one governed context layer, then deploys AI agents that search firm knowledge, draft proposals from past engagements and keep the CRM current. It is built for advisory, consulting, restructuring and accounting firms that have no data team, and OC delivers and runs it while your partners approve the work.
The problem, in the words we hear from firms
"We've done this exact engagement before. Nobody can find it."
Managing partners and COOs say some version of that line all the time. The firm has fifteen or twenty years of work product. The answer to "have we ever advised a lender group on a cross-border plan?" exists. It sits in a SharePoint folder named after a client code, in a partner's sent mail, in a BillQuick project with the hours split across three phases, and in a DealCloud record that was last touched in 2022.
So the question goes out by email to six partners. Two answer. The proposal gets written from the most recent similar deck someone remembers, which may not be the best one. And the CRM, which the firm paid real money to implement, drifts further from reality every week because updating it feels like admin with no payoff.
A better folder structure will not fix this. The knowledge is spread across systems that were never built to talk to each other, and the people who can connect the dots bill the highest rates.
Where firm knowledge actually lives
Most knowledge management tools for consulting firms are wikis. They ask your people to write things down a second time, in a new place. Adoption fades within a quarter because nobody bills for curating the wiki. We take the opposite position: the knowledge already exists, so connect the systems where it lives.
System | What it knows | What it cannot tell you on its own |
|---|---|---|
DealCloud or another CRM | Relationships, mandates, pipeline, who knows whom | What was actually delivered, or whether the record is still accurate |
SharePoint | Proposals, engagement letters, deliverables, models, memos | Which documents belong to which engagement, and which version won |
Outlook | The real history of a relationship and every scope change | Anything structured; it is the least searchable system the firm owns |
BillQuick or another billing system | Hours, fees, staffing and realization by project | The context behind the numbers: why a fixed-fee job ran over |
Excel | Pricing models, staffing plans, trackers kept by one person | Anything at all to anyone who is not that person |
The useful answer to almost any partner question needs three or four of these at once. "Show me restructuring engagements over the last five years where we advised the creditor side, what we charged, who staffed them and which proposal we used" touches the CRM, SharePoint, billing and email. That is the query OC is built around.
What OC does, step by step
Map the systems and the questions. We list the questions partners and operations staff ask most often and trace which systems hold each part of the answer.
Connect the systems into the brain. OC links DealCloud, SharePoint, Outlook, billing and spreadsheets into one knowledge graph we call the brain. Clients, engagements, people, documents and invoices become connected records, so "this deck" is tied to "this engagement," "this client" and "these hours."
Set governance first. Who can see what is decided before any agent runs. Engagement teams, practice groups and confidential matters are scoped with your operations and IT leads.
Deploy agents trained on how your partners decide. The agents learn from how your veterans pick precedent, scope work and price it, using your own past engagements as the examples.
Run it for you. OC operates and maintains the connections and agents. Your team reviews and approves what the agents produce. You do not need to hire a data engineer.
Three jobs firms start with
Firm knowledge search across SharePoint and CRM
A partner asks a question in plain English and gets an answer with links back to the source documents, the DealCloud record and the billing project. The answer cites where each fact came from, so a partner can check it in a minute instead of trusting it blindly. Firms often start here because it asks nobody to change how they work.
Proposal drafting from past engagements
When an RFP or a warm lead arrives, the agent finds the closest past engagements by industry, situation and size, pulls the scope language that was used, the staffing that was billed and the fee that was actually realized, and assembles a first draft in your firm's format. A partner edits it. The draft starts from what the firm really did, not from whatever deck was most recently saved.
CRM adoption without nagging
Plenty of firms have a CRM that the business development team believes in and the partners avoid. The agent reads Outlook and calendar activity and proposes DealCloud updates: a new contact, a meeting logged, a mandate stage change. A person accepts or rejects each one. The CRM stays current because the work of updating it moved from the partner to the agent.
What stays human
Every proposal, fee and scope decision. Agents draft; partners sign.
Every CRM change before it is written back.
Conflicts and independence judgments. The agent can surface related matters it finds, but the conflicts process your firm already runs stays the authority.
Anything that goes to a client.
A firm sells judgment. An agent that sends work to a client without review is a liability, however good the draft.
What to measure
Name the unit before anything is built. If a project cannot say what it will count, it will not show a return, which is the pattern behind most stalled AI pilots (see why AI pilots stall before EBIT). For professional services firms the countable units are usually these:
Proposals drafted from a cited precedent engagement, per month, and partner hours from RFP received to first draft.
Precedent questions answered with a source link, versus questions still sent around by email.
CRM records updated by agent suggestion and accepted, and the share of active mandates with a DealCloud touch in the last 30 days.
Realization on fixed-fee work where the proposal was priced from past billing data.
Pick one or two. Measure the baseline before go-live. Then compare.
How this compares with Microsoft Copilot and Glean
Many firms already pay for Microsoft 365, so Copilot is the obvious first question. It is a reasonable choice. Microsoft 365 Copilot works inside Outlook, Word, Teams and SharePoint, respects the permissions users already have, and offers more than 100 prebuilt connectors to outside systems such as Salesforce and Dynamics 365. Where no prebuilt connector exists, Microsoft documents a custom connector path that "requires a developer to define a schema, register the connection in Microsoft Entra ID, and write code to pull and push data" (Microsoft Learn, 2026). Microsoft also publishes guidance on finding and fixing overshared SharePoint sites before rollout, which is worth reading whatever you choose.
Glean describes itself as "an AI platform for work that unifies enterprise search, assistants, and agents on your company's context," with 275+ connectors including SharePoint, Outlook and Salesforce, and it enforces source-system permissions (Glean, 2026). For a large firm with an IT team ready to run a search platform, it is a serious option.
DealCloud itself now ships Intapp Assist, which adds generative AI to relationship, deal and outreach work inside the CRM (Intapp, 2026). If most of your knowledge lives in DealCloud, that may be enough.
Where OC differs: these products are tools your team configures and runs. OC is delivered and operated for you, connects systems that lack a prebuilt connector (check whether your billing system has one before you assume), and links records across systems into one graph, so an engagement is tied to its documents, emails and invoices. If you have the staff to configure a platform, buy one. If you do not, that is the case we wrote up in buy vs build an AI context layer.
How a project starts
It starts with a strategy call. We ask which questions eat partner time, which systems you run and what you would count to call it a success. If there is a fit, we scope one job (usually knowledge search or proposal drafting), connect the systems it needs and put it in front of a small group of partners. More jobs follow once the first one is used every week, not before.
Frequently asked questions
Do we need a data team to run this?
No. OC builds, connects and operates the brain and the agents. Your team's job is to tell us how good work looks and to approve what the agents produce. Many firms have an IT lead or a managed service provider and no data engineers. That is the situation this is designed for.
Can it connect to DealCloud, SharePoint, BillQuick and Outlook?
Those are the systems we hear about most from advisory and accounting firms, and connecting the systems a firm already runs is the core of what OC does. Specific versions, hosting (cloud or on-premises) and access methods vary by firm, so we confirm each connection on the first scoping call rather than promise it on a web page.
Do you copy all our documents into a new warehouse?
No. The brain is a knowledge graph that links records across your systems, and your systems stay the source of truth. What is indexed, how it is stored and who can see it is set during scoping with your IT lead.
How do you handle confidential engagements and ethical walls?
Access rules are set before any agent goes live. Confidential matters, practice groups and engagement teams are scoped with your operations and IT leads, and agents are limited to what those rules allow. Your existing conflicts process stays in charge. On security: OC is HIPAA-aligned and SOC 2 Type 2 aligned, with the formal audit underway and expected to complete before year-end.
We already pay for Microsoft 365. Why not just turn on Copilot?
You may want both. Copilot is strong inside Microsoft apps and respects SharePoint permissions. The harder part for most firms is linking SharePoint to the CRM and billing records so an answer can say which engagement a document belongs to and what it earned. If your systems have connectors and you have someone to configure and maintain them, Copilot may be enough. If not, OC does that work for you.
What happens after go-live if partners don't use it?
Then it failed, and we treat that as our problem. Usage is measured from the first week against the unit you picked. Heavily edited drafts and rejected CRM suggestions are feedback the agents are retrained on. A tool nobody opens is the most common way AI projects die, which is why OC runs the system after launch instead of handing it over.
Why not build this ourselves?
Some firms should. If you have engineers who can maintain connections to four or five systems, keep permissions in sync and retrain models as your work changes, building can make sense. Most firms do not, and the build costs keep coming after launch. We lay out both sides honestly in buy vs build an AI context layer.
Sources
Microsoft Learn, "Copilot connectors overview" (2026), accessed 6 October 2026: learn.microsoft.com/en-us/microsoft-365/copilot/connectors/overview
Microsoft Learn, "Get ready for Microsoft 365 Copilot with SharePoint Advanced Management," accessed 6 October 2026: learn.microsoft.com/sharepoint/get-ready-copilot-sharepoint-advanced-management
Glean, product overview (2026), accessed 6 October 2026: glean.com/product/overview
Glean, connectors (2026), accessed 6 October 2026: glean.com/connectors, with connector pages for SharePoint, Outlook and Salesforce
Intapp, "Intapp Assist for DealCloud" (2026), accessed 6 October 2026: intapp.com/dealcloud/ai
Book a strategy call to see this on your own firm.
Your systems, your documents, and what your people have been carrying around in their heads. Thirty minutes to see what an AI brain could look like in your company.
Book a strategy call
© 2026 OutcomeCatalyst