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Field Note

The AI brain your business is missing

Last month, a 40-person recruitment agency asked us why their best people spent half their day hunting for information. Six weeks later, anyone in the company could ask a question and get an instant answer pulled from every system they use. This is how we built it.

Published

Jan 10, 2025

Reading Time

8 min read

Topics

AIOperationsGrowthAutomation

Key Takeaway

You do not need a data warehouse or a team of analysts. You need an AI layer that speaks human and knows where all your stuff lives.

The moment we knew something was broken

Sarah runs operations at a recruitment firm. Forty people, growing fast, profitable. But every Monday morning, she watches her team do the same dance: digging through Bullhorn for candidate notes, searching Slack for that conversation about the client, opening six browser tabs to piece together a story that should take ten seconds to tell.

One day she timed it. Her senior recruiters—people billing six figures—were spending two hours daily just finding information. Not analysing it. Not acting on it. Finding it.

That is not a people problem. That is not a training problem. That is a systems problem. And it is killing businesses that do not even know they have it.

The real cost of scattered knowledge

Here is what nobody tells you about growing a business: the more successful you get, the more your knowledge fragments. You add tools. You add people. You add processes. And slowly, the left hand stops knowing what the right hand is doing.

We have seen it everywhere. The sales team closes a deal but support has no context. The founder knows the answer but is stuck in meetings all day. The new hire asks a question that five people could answer, but nobody knows who.

Most businesses try to solve this with wikis, documented processes, or weekly all-hands meetings. None of it works. The wiki goes stale. The processes live in someone's head. The meetings become a chore.

The answer is not more documentation. It is an AI that reads everything and answers anything.

What we actually built

We connected the recruitment firm's entire digital footprint to a single AI brain. Bullhorn CRM. Google Drive. Slack. Their email. Their internal wiki. Everything.

Now when a recruiter asks "What do we know about Acme Corp?" they get a complete picture in seconds: past placements, billing history, key contacts, recent conversations, even that note someone left in Slack about the hiring manager's preferences.

When the ops team asks "Which contractors are ending assignments this month?" they get a list pulled live from the system, with context about each relationship and suggested next steps.

When a new hire asks "How do we handle IR35 assessments?" they get the actual process, not a link to a document that may or may not be current.

The part everyone gets wrong about security

The first question every founder asks: "Is this safe?" Good. You should ask that. But the answer is simpler than the enterprise vendors want you to believe.

You do not need a six-month security audit. You do not need to hire a CISO. You need three things: your data stays yours, access matches what people can already see, and there is a record of who asked what.

We build it so the AI respects your existing permissions. If a recruiter cannot see finance data in your CRM, they cannot ask the AI about it either. If someone leaves the company, their access disappears. Simple.

Your data never trains public models. Your conversations stay private. And if a client ever asks how you handle their information, you have a clear answer.

Six weeks from zero to "how did we live without this"

We did not spend months planning. We did not write a requirements document. We started with the pain.

Week one: We mapped where the team actually spent their time hunting for information. Three systems accounted for eighty percent of the problem.

Week two: We connected those systems to the AI layer and let Sarah's ops team start asking questions. They found gaps. We fixed them.

Weeks three and four: We expanded to the full team. More questions revealed more edge cases. The AI got smarter with every conversation.

Weeks five and six: We polished the rough edges, trained the team on what worked, and documented the patterns that emerged.

By week six, people had stopped asking "Where do I find X?" They just asked the AI. The two hours of daily searching? Gone.

Why this matters more for growing companies

Big companies have armies of analysts, dedicated IT teams, and million-dollar data warehouses. They can afford the brute-force approach to knowledge management.

Growing businesses cannot. You need your best people doing their best work, not playing digital archaeologist. You need new hires productive in days, not months. You need the founder's knowledge accessible even when they are not in the room.

An AI layer gives a forty-person company the institutional memory of a company ten times its size. Every conversation, every document, every decision—findable in seconds by anyone who needs it.

The businesses that figure this out in 2025 will have a permanent advantage. The ones that wait will keep losing hours to the hunt.

Next Steps

Move fast without breaking trust

Time the hunt

Ask your team to track how long they spend searching for information this week. The number will be higher than you expect.

List the sources

Write down every place your team looks for answers: CRM, docs, chat, email. That list is your starting point.

Pick the biggest pain

Find the question your team asks most often that takes the longest to answer. That is where you start.

Ready to turn this into a scoped engagement?

We help teams implement these approaches with hands-on execution, not slide decks.