Every company will soon have access to the same AI. The advantage goes to whoever gets their operation in order first: the systems, the records, and the know-how living in people's heads. We do that groundwork, then put AI on top to run it.
Most teams want to jump straight to agents and automation, the visible payoff. But AI can only act on what it can reach and trust. When the knowledge is scattered across systems and living in people's heads, the AI has nothing solid to stand on, and the project stalls. The work that makes AI pay off is the unglamorous part: getting your operation's knowledge into one place and keeping it true.
The order matters more than the technology. Each phase only works once the one before it is solid.
Pull in what runs your business today: current systems, historical records, and the know-how living in your team's heads.
Wire in the connections and processes that keep the data fresh automatically. You touch it once, and the system keeps it true from then on.
Agents, automation, and instant answers, built on a knowledge base that stays right. This is where the higher levels of AI come alive.
Everyone wants to start at Phase 3. The payoff only compounds if the knowledge is seeded right and stays current on its own. That is the part we build for you, so the fun part actually works.
Different shapes, one discipline: grounded in your data, scoped with guardrails, and a person in the loop.
One connected system that runs on your operation's knowledge and data, with agents and automation on top. We run our own company on one.
Agents that do real work in your workflow, with guardrails and a person in the loop.
Models grounded in your own data, built into your systems.
Agents that run the workflows your team does by hand, across systems that don't talk to each other. Scoped, logged, reversible: the agent proposes, your people decide.
Getting the data in shape so AI is grounded accurately, then a system that maintains that accuracy. It underpins everything above, and it is phase one of how we work.
Phases one and two are business analysis. Mapping how your operation really runs, finding where the knowledge lives, and getting it into a shape a system can use. It is the same Requirements by Design work we have done since 1993, now aimed at making AI useful. The AI on top is powerful, and it comes last rather than first.
You will see the plan and approve the number before anything gets built. We map your operation first, commit the fixed bid in the room, and put AI to work only once the foundation is solid. See how we work →
We did not build this offering from a whitepaper. Counterpart runs its own sales, delivery, and back office on a custom AI knowledge system, one source of truth that stays current on its own. We learned what it takes on ourselves first, then turned the approach into something we can build for you.
Counterpart runs its own sales, projects, and finance on a custom AI knowledge base. We built it, we run on it every day, and it is where this offering came from.
One source of truth the whole team queries in plain language. It drafts from context, surfaces what is due, and stays current on its own instead of going stale.
We consolidated 11 separate systems into one source of truth for Indiana's financial aid: the silo-busting groundwork any AI operation has to start from.
Describe the systems, the spreadsheets, and the knowledge that lives in people's heads. We'll reply within a business day with how we'd get it in order and where AI fits.