Densery
Densery SolutionsFrom “we should automate this” to an agent on schedule.
Describe the job. The agent designs the workflow, writes the code and tests it against your data. The platform runs it on your schedule, with a person in the loop where you say so.
Agents fail in production for three reasons: no context, no environment, no evidence. We built one platform for all three.
Designed in chat. Run by the platform.
The workflow the agent wrote, the schedule it runs on, and the gate where a named person still decides.
above the 0.85 threshold · autonomy widens as scores hold
What changes for your team.
Design in chat or on the canvas
Describe the job in words or draw it. The agent turns it into a workflow you can read.
Code steps, sandboxed
Machine learning and optimisation as code, executed in isolation rather than trusted.
Approval where it matters
A person in the loop exactly where you say so, and nowhere else.
Evaluate, then trust more
Eval scores per run. Widen autonomy as the scores hold.
Pilot design · not a customer
Delivery runs, re-planned every two hours.
A logistics company's drivers, trips and orders already live in the ontology. A planner asks for an optimiser. The agent writes it, the platform runs it every two hours in a sandbox, the dispatcher approves changes above a threshold, and the plan lands in the TMS.
Opportunity
Internal help desk that acts.
Answers from policy and the ticket system, then the action: reset, approve, escalate — each one classified and logged.
What connects to this.
Thirty minutes with Densery.
Tell us about the work you want an agent to finish. We listen first, then show you the platform and the case that is closest to yours. This is a working session, not a sales pitch.