Overview
Agents that plan, use your tools, and complete real tasks end to end, with the checks that make them safe to leave running.
Most automation breaks the moment a task needs judgement. Scripts follow rules, and the real world rarely sticks to them, so your team keeps absorbing work that is repetitive but not quite mechanical.
How Devyst Approaches It
We start from one workflow that is costing you real hours, and build an agent that owns it end to end: connected to your live systems, bounded by explicit rules, and logged so you can see exactly what it did and why.
What Gets Delivered
Engagement Process
- 01
Map the workflow
We follow one process end to end and mark exactly where judgement is required and where it is not.
- 02
Build and evaluate
The agent is built against a fixed test set, so we can prove it improved rather than assume it.
- 03
Ship with guardrails
It goes live behind limits and logging, starting supervised and widening as it earns trust.
Use Cases
Proposal and quote generation
Professional ServicesReads the brief, pulls from past work, and drafts a tailored response in minutes.
Document intake
Financial ServicesExtracts structured data from incoming paperwork and routes anything uncertain to a person.
Frequently Asked Questions
A chatbot answers. An agent acts: it calls your systems, changes state, and reports what it did. The engineering is mostly in the guardrails around that.
Every action is logged with its inputs and reasoning, and anything below a confidence threshold goes to a human queue instead of proceeding.