Applied AI · Enterprise and financial services
The models are fine. The data underneath has no structure and no shared meaning, so nothing built on it holds up. We start from the business problem, build down to the data that supports it, and stay until it runs.
What we do
Three of these build the system. The fourth takes it to market. We can take a program from a blank page to something running in production. We work directly with enterprises, and we work behind other consultancies and technology vendors who need this depth on a program.
We scope where AI actually changes your numbers, then build it against your real data and put it in front of real users. If the honest answer is that you shouldn't build it yet, that's what we'll tell you.
A live layer connecting entities, claims, and evidence across your systems, so every answer traces back to a source. We're practitioners here. We deploy and work with ontologies to give the graph shared meaning, and we bring in our extended team of experts when the work calls for it.
Agents with clear jobs, real tools, and guardrails. Built to run inside your workflow, with a person accountable for the decision at the end of it.
This works in two directions. Outside, we position technical products for enterprise buyers, tighten the pricing, and set up the pipeline motion. Inside, we get your own product, sales, and engineering teams telling the same story about what you're selling and why it wins, which is usually where the trouble starts. We've carried the number at enterprise software companies and sat on the buying side, so the advice comes from having done both.
Every failed program we've walked into started with a platform decision instead of a business problem.
Meridian7 · Founding principal
How we work
Most firms in this space are tech shops working bottom up. They build the platform, then go looking for a use case. We work the other direction. We find where the value actually sits, make sure it's real, then build down into the data that supports it.
We start with the decisions that are slow or expensive and what it's worth to fix them. If the number doesn't hold up, we say so before anyone writes code.
Then we work down into the structure. The graph goes into production against live systems, with ontologies giving it shared meaning, shaped by the problem rather than by the tooling.
Agents and applications reason against grounded context and act inside your workflow. We stay until it holds up under real load.
How we engage
Every engagement is scoped before it starts and staffed with senior people only. You'll know what it costs and what it ends in before you commit.
We look at the problem, the systems, and the data behind it. Then we tell you whether the value case holds up and what it would take to build.
We design the layer and put it into production against your live systems. Your team works alongside ours the whole way, so it doesn't leave when we do.
Senior judgment on call for teams already building. Architecture reviews, vendor decisions, positioning, and the conversations you'd rather have before the board meeting.
The firm
Meridian7 is an applied AI firm. We work with major enterprises, other consultancies, and technology companies building in this space. Two principals, forty years between them, on both sides of the enterprise table.
Between us we've held C-suite and senior leadership roles at every stage of company, from startups through mid-tier to major enterprises. We scaled go-to-market at enterprise software companies through IPO. We've also sat in the buyer's seat, evaluating platforms and committing budget inside a global investment bank and a Fortune 50 technology firm.
We've shipped production knowledge graphs in regulated environments, and we've led the go-to-market for the platforms built on top of them.
That combination is the whole point. The same team that builds your graph can tell you how it'll be bought.
We won't take on a program where nobody on your side can validate the output. That surfaces in week eight otherwise, and we'd rather find it in week one.
Contact
A short call is usually enough to know whether we can help. If we're not the right fit, we'll say so and point you somewhere better.