Every consulting firm I talk to has a version of the same problem. Win rates are decent. Client work is good. And yet the partners are exhausted, the margins are thinner than they should be, and nobody can quite explain where the hours go.

I can tell you where they go. They go into rebuilding things the firm already built.

If you run a consulting or advisory business doing somewhere between $1M and $25M in revenue, you’re carrying a specific kind of overhead that doesn’t show up as a line item on your P&L. It shows up as senior time. Partner time. The most expensive hours in the building, spent on work that a well-built system could do in a fraction of the time.

We usually see firms this size losing somewhere between $80,000 and $300,000 a year to this exact pattern. Not from bad clients or bad delivery. From the gap between what your firm already knows and what it can actually retrieve and reuse.

Where the Hours Actually Go

Proposals eat the senior team alive. A major proposal at a mid-size firm takes 20 to 40 hours to put together, and most of that time comes from the people billing at the highest rates. Someone is digging through old decks looking for a case study that fits. Someone is rewriting the same methodology slide for the eighth time this year, slightly differently each time because nobody can find the last version. Your win rate might be fine. Your cost of sale is not. Every hour a partner spends assembling a proposal is an hour they’re not spending on billable work or on the next pitch.

Research gets repeated across the firm without anyone noticing. Every new engagement starts with two or three weeks of secondary research. Industry structure, competitive landscape, regulatory backdrop, key players. Some analyst or associate builds this from scratch, even though a different team at your own firm did nearly identical research for a similar client eighteen months ago. Nobody flags it because nobody has visibility across the firm’s history of work. That’s not a research problem. That’s a retrieval problem, and it compounds every time you take on a new client in a sector you’ve already touched.

Knowledge management debt is the quiet one. Every project your firm delivers produces real intellectual property; frameworks, findings, client-specific insight, transcripts of interviews that took real effort to arrange. Almost none of it is reusable. It lives in a folder, in someone’s inbox, in a deck that only the original team ever opens again. When a new engagement needs that exact insight, the firm builds it a second time and pays for it a second time. You already own the answer. You just can’t find it.

None of these three pains are dramatic on their own. Together, over a year, across a firm doing multiple engagements at once, they’re the difference between a good margin and a mediocre one.

What an AI Agent Actually Does Here

This is the part people usually get skeptical about, so let me be specific rather than vague about it.

The Proposal Generation Agent we build inside Omni ops sits on top of your firm’s actual history. It pulls from your past proposals, your case studies, your pricing structures, and your win/loss patterns, and produces a tailored first draft the moment a new opportunity comes in. Not a generic template. A draft that already reflects how your firm actually talks about its work, with the right case studies surfaced automatically because they match the client’s sector and problem type. Your team still edits it. They still add judgment and relationship context a machine doesn’t have. But they’re editing a strong draft instead of staring at a blank deck at 9pm the night before a pitch.

The Research Agent runs structured industry and company research the moment a new engagement kicks off. It pulls from public sources, summarizes the relevant findings, and produces a one-page brief with sources attached, ready before the kickoff call instead of two weeks into the engagement. If your firm has touched the sector before, it also surfaces the internal research your own team already did, so nobody starts from zero on something the firm already knows.

The Knowledge Agent is the one that changes how the firm compounds over time. It reads every deck, every document, every meeting transcript your firm produces, and lets anyone at the firm ask a question across that entire corpus. “Have we ever pitched a supply chain transformation to a mid-market manufacturer?” “What did we find last year on pricing strategy in healthcare services?” Instead of a slow scavenger hunt through old folders, someone gets an answer in minutes, with the source document attached.

None of these three agents replace your team’s judgment. They replace the hours your team spends rebuilding things that already exist inside the firm. That’s a very different kind of automation than most people picture when they hear “AI agent.” It’s not client-facing. It’s not flashy. It’s the operational layer underneath the work your partners are already doing.

If you want to see how this fits together for a firm your size, see Omni for consulting firms walks through the specifics without the generic AI-vendor pitch.

The Dollar Math for a $1M-25M Firm

Let’s put real numbers against this, using ranges that are typical for firms of this size rather than any single firm’s exact figures.

Add in research that gets repeated across engagements because nobody had visibility into what the firm already knew, and you’re looking at another meaningful chunk, often in the same range, depending on how research-heavy your typical engagement is. Add the knowledge debt, the projects where a team spent three days rebuilding a framework that existed in a folder two floors away, and the $80,000-$300,000 range we quoted earlier stops feeling abstract.

This isn’t money you’re losing to bad clients or bad delivery. It’s money you’re paying twice for work you already own. That’s the frustrating part, and it’s also the part that’s fixable without a re-org or a new hire.

What the Omni Audit Actually Looks Like

I built the Omni Audit because most firms don’t need another 40-page AI strategy deck. They need to know, specifically, where their hours are going and what a fix actually costs and delivers.

It runs 60 minutes. No slides. Three outputs at the end:

1. A map of where your proposal, research, and knowledge work actually happens today, and where the hours are concentrated.
2. A realistic estimate of what that’s costing you annually, based on your actual engagement volume and team structure, not a generic industry number.
3. A short list of which agent, or combination of agents, would move the needle first for your firm specifically.

No deck. No sales pitch disguised as a workshop. Just a clear picture of the gap between what your firm knows and what it can retrieve, and what closing that gap is worth.

If you’re the owner or managing partner looking at your team’s hours and wondering why the margin doesn’t match the effort, this is the fastest way to find out. Book a 60-min Omni Audit and we’ll walk through your specific numbers, not a template.

Getting Started Without Betting the Firm

You don’t need to automate your whole operation in one move, and I’d tell you not to try. The firms that get the most out of this start with one agent, tied to one specific bottleneck, and prove it out before expanding.

If proposals are the pain, start there. If it’s research that’s eating the analysts, start there instead. The order matters less than starting somewhere real, with a clear before-and-after you can measure in hours saved and win rate held or improved.

We put together a practical worksheet for exactly this moment, called Deploy Your First Business Agent. It walks through how to pick the right first agent for your firm, what to expect in the first 30 days, and the questions to ask any vendor promising to automate your knowledge work. You can download it directly here and use it before you talk to anyone, including us.

For a broader look at how this fits into the rest of your operations, our guides section covers the mechanics of agent deployment in more depth, and the Omni ops page breaks down the categories of work these agents typically handle across different firm structures. If you want to see how other service businesses are thinking about this, our insights library has more real-world detail than most AI content you’ll find elsewhere.

The math doesn’t lie. If your firm is doing $1M-25M and running the typical mix of proposals, research, and project delivery, you’re very likely sitting on $80,000-$300,000 a year in recoverable hours. Not hypothetical hours. Hours your senior people are spending right now, rebuilding things the firm already knows.

The fastest way to find out exactly how much, and what to do about it, is still the same. See Omni for consulting firms for the specifics, or go straight to booking your Omni Audit and we’ll get you real numbers within the hour, not a follow-up call three weeks from now.