Automation that goes beyond scripts: workflows, language models and agents that pull knowledge from your data and genuinely take work off your plate. Descend — from the trigger to the agent team.
Trigger
Recurring work runs by itself: an event — an email, a form, a new record — starts a workflow that fetches, checks and hands data on. No copy-and-paste, no forgotten steps.
Model
Language models where they take work off your plate: understanding documents, summarising content, triaging requests. We connect them to your data — with clear limits on what they may see and do.
Collaboration
For multi-step tasks, specialised agents work together: one researches, one checks, one executes — and the result flows back into your process in order.
Next step
Tell us which process costs you time — we show where automation really helps and where it does not.
Process
We look at which work costs you time — and show where automation really helps and where it doesn't.
We connect workflows and language models to your existing tools, data and documents — with clear limits on what they may see and do.
Rules, approvals and human oversight sit where they matter. Every run stays traceable.
We accompany the launch in real operations and fine-tune until the workflow runs reliably alongside your team.
Common questions
An automated sequence: a trigger — an email, a form or a new record — starts a chain of steps. Language models handle tasks such as understanding, summarising or classifying; fixed rules take care of the rest.
Recurring work with a clear pattern: pre-sorting requests, analysing documents, summarising content, moving data between tools. For multi-step tasks, specialised agents work together.
Usually, yes. We build workflows on the tools you already use and connect language models to your existing data and documents.
We define up front which data a model may access and what it may do. Data protection and access rights are part of the plan from day one, not an afterthought.
The goal is to take recurring work off their plate. Where decisions matter, a human stays in control — for example through approvals in the workflow.
That depends on the process and the systems involved. In an initial call we clarify where automation pays off and turn that into a concrete proposal.