Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
From the blog
Adoption Across San Francisco, New York, Boston, and Austin perspective on NIST's AI Risk Management Framework 2.0 incorporates agentic AI, multi-agent systems, and tool use into its risk taxonom
Adoption Across London, Bangalore, Singapore, and Tokyo perspective on Sierra's funding momentum signals the customer-experience agent category has crossed from experiment to enterprise budget li
Adoption Across London, Bangalore, Singapore, and Tokyo perspective on Where the leading autonomous coding agents stand on SWE-bench Verified after the April 2026 model releases.
Adoption Across San Francisco, New York, Boston, and Austin perspective on Vapi 2.0 added a visual workflow builder, multi-agent 'squads', and OpenTelemetry-grade observability — closing real gap
Adoption Across San Francisco, New York, Boston, and Austin perspective on AI SDK 5 introduces first-class agent loops, MCP support, and a new generative UI runtime.
Scout's 10M-token context is a record — but does it actually work at the long end? Independent benchmarks say mostly yes. Practical context for teams in Dallas, TX.
How Gemini 3 Pro's tool use compares to function-calling on Claude and OpenAI, with code samples and latency numbers. Practical context for teams in Mountain View, CA.
NotebookLM Pro adds custom research agents, Audio Overviews v2, and a 5M-token corpus per notebook — here is what changed. Practical context for teams in San Francisco, CA.
Three consumer chat apps — Le Chat, ChatGPT, Claude — compared on UX, agents, and pricing in 2026. Practical context for teams in Tel Aviv, Israel.
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