What a Unified Agentic AI System is.

A Unified Agentic AI System is one intelligence that runs across a business, built from coordinated AI agents that share memory between runs.

That is the definition. Here is what it looks like on the ground. Most companies we walk into already own a drawer full of AI tools. One writes emails. One summarizes a report. Another has sat unused since the demo. None of them know what the others did yesterday, so work still slips through the gaps between them. A unified system closes those gaps. The agents remember, they pass work to each other, and they get sharper at your business the longer they run.

Where most AI gets stuck

In a regulated company, AI usually arrives one tool at a time. Someone buys a bot for the sales inbox. A scientist tries a model on one report. Each tool lives outside the systems where the real work happens, the QMS, the LIMS, the MES. The team at Outsourced Pharma said it cleanly: tools that sit outside those core environments make one task a little faster and change nothing else. We have watched it play out in every audit we have run. The win is real but small, and it does not compound.

A unified system shares one memory across the agents. What one of them finishes becomes the starting point for the next, so each run comes back a little faster than the last because nothing has to start cold.

How deep you go

You do not buy the whole thing on day one. Most clients start with a single workflow, watch it for a month, and add the next piece once they trust it.

• Agentic Workflow. One workflow, start to finish. $5,000 to $15,000. You can measure it inside 30 days.
• Agentic OS. Three to seven agents working together, sharing memory, reviewed every week. $20,000 to $60,000.
• Unified AI System. One intelligence across the whole company, still learning after we hand it over. $60,000 and up.

See how the pricing works.

Where we build it

The architecture holds whether you make drugs or detail cars. The work underneath is different, so the agents are too.

• AI consulting for pharma
• AI agents for CROs
• AI agents for CDMOs
• AI for clinical operations
• AI for regulatory affairs

One we shipped

A CDMO came to us with quote requests piling up faster than one scientist could answer them. We put stoichiometric quoting and literature search on an Agentic OS. It returned $264,000 in the first year on a $20,000 build. Because the agents kept context between quotes, the work got faster every week instead of starting cold each time.

CDMO build. $264,000 first-year saving. $20,000 build.

Common questions