Where a general assistant runs out on company work
The gaps show up in the same order at almost every business we work with. The assistant has no persistent context, so the first two minutes of every session go on explaining what the company does and which deal you mean. It cannot reach the systems where the answer actually lives, so someone gathers the documents by hand and pastes in a subset small enough to fit. The answer that comes back is fluent and unsourced, which means a person has to go and verify it before anyone will act on it. There is no structure holding any of this, so nothing accumulates. Ask the same question next month and the work starts again.
Nothing runs on a schedule and nothing acts
A chat product waits to be typed at. Most of the work worth automating is the other kind: the weekly portfolio update that pulls the latest operating numbers, the pipeline review that flags what has gone quiet, the diligence checklist that runs itself against a new data room overnight. Those need something that wakes up on its own, reads from a record, writes back to it and tells a person what changed. That is a different shape of software, and it is the shape most of what we build takes.
The knowledge stays with the person, not the company
Every good answer an assistant produces lives in one individual's chat history. The analyst who worked out how to frame the question keeps that value, and it walks out with them. This is the same problem as the one in the case studies: institutional memory that lives in heads and inboxes rather than in anything the next person can query. A shared record is what turns one person's work into something the business owns. We go deeper on that in why AI needs a system of record.
Governance is answered per seat, not per company
Consumer and per-seat plans answer data questions at the level of the individual subscription. For a business handling confidential deal material, operating data or anything under a client agreement, the questions that matter are company-level ones. Where does this sit, who inside the firm can reach it, and what happens when someone leaves. DealSage runs on DealSage Cloud, in a private VPC or on-premise, with access set by you and every answer logged.
It stops at the answer
This is the one people underrate. An assistant hands back an answer and the work of turning that into something the business runs on is still ahead of you. Someone has to decide which workflow is worth changing, build it, connect it to real data, and get the team to use it. That is what we do, and it is why how we engage starts with finding the problems worth solving rather than with a login.
Most firms end up running both
DealSage connects over MCP, so ChatGPT, Claude or any model your team prefers can query your structured company record directly. One private equity client did exactly that: they kept their existing AI assistant and subscriptions, and we put DealSage underneath. The team asks questions in the tool they already use, and gets answers drawn from five years of deals, each cited back to the document it came from. Nobody had to change their habits. The assistant simply stopped starting from a blank page. You can see the shape of that on the platform page.