Our point of view
Every month the models get better and a new tool launches. That was never the bottleneck. The hard part is human: getting busy people excited to change how they work, integrating AI into the workflows they already have, and building the judgment to know when to trust it.
The models improve every month, and a new tool launches every week. None of that is the constraint. The constraint is people, habits, workflows, and the judgment to use AI well. Pretending the next model release will fix that is how most AI initiatives stall.
Coaching people until they're fluent, not just trained. Getting them excited rather than wary. Integrating AI into the daily work instead of bolting it on. Teaching your team to push tools like ChatGPT, Claude, Harvey, and Legora well past the obvious, and giving you a straight answer on what's worth buying. When it's time to build, we don't start from a blank page: we deploy from a catalog of ready-to-run Skills and a menu of tested agents, each one tuned to your team's playbook. This is the work we do first, and it matters most early on.
As more of the day-to-day runs on AI and agents, trust becomes the question. Is what your AI agents are doing consistent with your policies, your obligations, and your risk tolerance? We're building toward that layer, but it's earned through the hands-on work, not sold as another dashboard.
Right now we're building a contract intake agent for a publicly traded ad tech company, a privacy review agent for a fintech, and an AI evaluation and training program for a public energy company. We'll deploy agents like the one below for your team too.
Start with a fixed-price, six-week pilot on one or two workflows.
Book a 30-minute intro call