dezent digital GmbH provides agent engineering and infrastructure services to integrate AI agents into enterprise applications. Offerings include intent engineering, context infrastructure and runtime design, trace‑based observation and EvalOps, and development and maintenance of reusable agent skills and refinement cycles.
Team training: translate ambiguity into clear specifications, define behaviour for agents, and use spec.md templates for executable contracts.
Context Infrastructure
The accelerated middle: structure secure access to the codebase, APIs and documentation for AI tools so implementation runs in a controlled and efficient way.
Observation & EvalOps
Systems for tracing agent decisions, detecting drift and catching edge cases; data-driven reliability rather than only code review.
Production Refinement
Monthly retainer: analyse production traces, update prompts from real edge cases and continue the Build-Test-Ship-Observe-Refine cycle.
Intent & Runtime Design
Define triggers, skill allowlists and sub-agent boundaries; specify when agents delegate and which tools they are allowed to use.
Context Architecture
Context compaction, progressive disclosure and sandboxed Python environments for safe execution; make agents more robust against large files and long conversations.
Trace-based EvalOps
Log decisions and tool calls, detect token-limit hits and incorrect tool usage, and catch intent drift before production failures.
Skill Library Development
Turn repeated failures into reusable agent skills, e.g. PDF parsing, Jira formatting or Slack integration, as a corporate skill library.
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