Hope Technologies
AI agents and workflows, built to fit how you work.
Most workflows don't need a chat window. They need a language model at the right step, and a way to see what it did. We build pipelines like that and bring them in alongside the way you work now.
What we do
Agents, adoption, and development
- Agent systems and workflows. Chat assistants where conversation helps, and pipelines that run on their own where it doesn't, with a language model at the steps that need one. Much of our work is in healthcare: pipelines and chat over documents and insurance benefits. Where the data is sensitive, steps like OCR can run locally on small models, so it stays on your machines. Access is limited to what the job needs.
- Helping teams adopt agents. We guide your team in bringing agents into their work, and teach them how agents work, where they go wrong, and how to check them, so their trust rests on what they've seen.
- Custom development. Software, integrations, and automations, plus sites and CMS work. Built with coding agents and reviewed by us. After launch we maintain it, or hand you the same workflow so your team can.
Adopting agents
Start alongside, hand off in parts
There's a gap between what people do today and what they'd trust an agent to do. Seeing what the agent actually did closes it, one task at a time.
- Work as you do now. The agent runs alongside your process, and how you work doesn't change.
- See the work. Every step the agent takes is visible, and you compare it to your own. You stay in control.
- Hand off the parts that hold up. The routine pieces move to the agent. You keep the judgment calls.
An example. A site built in Elementor can work this way. The agent connects to Elementor directly (through an MCP server, a standard way for agents to use other software) and makes changes in the editor your team already uses. A person reviews each change on screen. A worklog shared between the agent and the team records what was done and why, and either side can add notes.
Agent pipeline
Dental insurance verification
Front-desk staff spend minutes per patient confirming dental coverage by phone. We built a pipeline that does it from a photo of the insurance card.
A vision model reads the card. The pipeline checks the fields, sends an eligibility request, and lays out the patient's benefits by procedure code. Each stage shows as it runs, with what the model read off the card and the raw eligibility response underneath, so staff can check any answer.
A chat assistant sits on top. Staff ask it things like whether a crown is covered or what the frequency limit is, and it answers only from the returned benefit data. When the answer isn't in that data, it says so.
It's a demonstration built on synthetic cards and a test eligibility service, with no real patient data. Each model has one narrow job and sees only that job's data, so either can run locally or on a secure cloud service.
History
Web development since 2011
Hope Technologies started in 2011. For years the work was web development, mostly for marketing companies that needed it built outside their own shop. Most of our clients now are small businesses, and we work with agents as well as websites.
Founder
Landon McLain
Landon started Hope Technologies in 2011 and has been building for the web since. He now builds agent systems and writes about how they work at landonmclain.com.
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