Agent runtime
Tool-calling, memory boundaries, approval flows, retries and escalation paths.
Developers
Architektur fuer Agenten, RAG und produktive ML Systeme.
ArchitectureKlare Systeme unter einer weichen Oberflaeche.
System architecture
Von Daten zu Tools zu kontrollierter Autonomie.
Wir bauen mit sauberen Schnittstellen, Evaluations, Logs und Betriebsmetriken, damit AI produktiv und pruefbar bleibt.
APIVector storeAgent runtimeEval harnessObservability
Technical capabilities
Talk stackRAG pipelines
Chunking, embeddings, retrieval evaluation, citations and permissions.
Model evaluation
Golden datasets, regression tests, quality scores, latency and cost benchmarks.
Integrations
CRM, Slack, email, calendars, knowledge bases, databases and internal APIs.
ML Ops
Monitoring, drift checks, logging, analytics and human feedback loops.
Security model
Role-based access, audit trails, data minimization and controlled automation.
Deployment map
ScopePrototype
Connectors
Evals
Governance
Production