AI Radar
Technology Adoption Radar
Where each AI capability sits on DarwinCX's adoption journey, from early watching to org-wide standardization.
Watch
Monitor, not yet acting
UI-operating agents (computer use)
Agents that drive existing software UIs directly. Promising but early; needs guardrails.
Self-hosted open-weights models
Near-frontier open models for cost and data residency. Watching quality vs hosted.
Experiment
Actively piloting
Low-latency voice agents
Speech-to-speech with tool calls for contact-center agent-assist.
Durable agent orchestration
Stateful, human-in-the-loop agent runtimes for oversight-heavy CX flows.
Adopt
Rolling into production
Prompt caching on Bedrock
Large cost reduction for repeated-context summarization. Ready to adopt.
AI pair-programming in engineering
Copilot-style assistance already lifting team throughput; expanding usage.
Standardize
Default building block
LLM summarization pipeline
Core VoC summarization is proven, in production, and our default building block.
Provider-agnostic LLM abstraction
Single interface across OpenAI/Anthropic/Bedrock is the org standard for all new AI features.