Leena AI

Two years ago it took us 187 days to put a customer's first AI Colleague into production. We got it to 43. Then it stopped, no matter what we shipped. So we looked at why, and it wasn't the product. Every automation still passed through four people. Someone who knew the process. Someone who knew how the systems connect. Someone to test it. Someone to fix it when it broke. Each one waiting on the one before. Most enterprises I talk to have the same shape, usually worse. One or two people learned the platform properly, and every request from HR, IT and finance queues behind them. They bought an agentic AI platform and got a bottleneck they pay for every year. Capability isn't the constraint any more. Within a year every platform will build you an agent from a description. What won't converge is the operating model: who builds them, and who keeps them running. Building one agent is a project. Operating dozens is an operating model. So we built an AI agent that owns the whole lifecycle. It plans the work, builds the AI Colleague, the tools and the connections, tests them against real systems, and repairs them when they break, inside the same permissions and approvals as the person who asked. That's Forge, live today in the Leena AI platform. The measure isn't how fast your best engineer builds something in a demo. It's how long it takes to reach production, and how many of your process owners have ever taken one there themselves.

A night-shift nurse gets a call at 3AM: there’s a family emergency. She needs to know if she has enough PTO to leave now, but HR won’t be in until 8AM. Rolling out an AI assistant to 51,000 employees was the answer to her problem. But getting people to use it was the hard part. In this on-demand webinar, Jessica Hendrix from CHRISTUS Health walks through how her team did it, from road shows at every location to writing the assistant into new-hire orientation.

Most HR teams don't need more headcount. They need to stop run-of-the-mill asks from clogging their inbox. At Coca-Cola, AskMi now handles the basic asks all on its own. Routine questions, policy lookups, PTO requests, and more now get resolved in seconds, 24/7/365. The net effect? Approval times have fallen 40% and 87% of tickets are resolved automatically.

Coca-Cola already added the box. "AskMi" sits in their HR org chart as a full team member - resolving 87% of employee queries end-to-end, reporting for duty since day 45. The case study shows what the org looks like after: what AskMi owns, what the humans got back, and the numbers.

Getting an AI assistant approved, integrated and launched feels like the finish line. But the bigger problem comes the day after: getting employees to actually use it. The Enterprise AI Adoption Playbook distills six plays from CHRISTUS Health’s rollout to 51,000 employees across 60+ hospitals: how they won first use, earned sign-off from security, legal and compliance, and tracked the metrics that matter.

Most HR support assumes people are sitting at a desk. Coca-Cola's workforce mostly isn't — so AskMi, their new AI colleague, stepped in and started processing routine requests. The impact went beyond a more convenient experience for their employees. It's 87% of requests never needing a human touch, approvals going through 40% faster, and an HR ops team finally getting its time back.