BAND builds enterprise-grade interaction infrastructure for distributed AI agents. Its platform enables real-time, multi-peer collaboration across agents and humans, while providing a runtime control plane that enforces policy, authority boundaries, and visibility across heterogeneous systems.
BAND supports developers, engineering teams, and enterprise platform leaders operating multi-agent ecosystems across internal systems, SaaS platforms, and partner environments.
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Dialpad Contact Center is Dialpad's AI-native platform for customer experience — the connective layer where conversations, intelligence, and action come together in real time.
At its core, Dialpad Contact Center is the world's first Agentic AI contact center: AI agents that don't just transcribe or summarize, but reason, resolve, and act autonomously across the full customer journey. Instead of routing customers between disconnected tools, Dialpad Contact Center unifies voice, digital, and human agents in one platform, connecting the voice and data silos that have historically kept support teams siloed and reactive.
Every interaction becomes part of a compounding intelligence layer. With 775M+ AI recaps and counting, Dialpad Contact Center turns each conversation into operational insight that improves resolution rates, agent productivity, and CX outcomes over time. That intelligence is continuously optimized, governed, and made visible across your organization through Dialpad's Guardian safety layer, ensuring secure, enterprise-grade AI operations at scale.
Dialpad Contact Center is built to resolve up to 80% of issues autonomously, reducing operational complexity while giving human agents the context they need for what still requires a human touch. People stay at the core; intelligence sits at the edge, ready to act the moment it's needed.
Rather than asking enterprises to take autonomy on faith, Dialpad Contact Center is validated through Dialpad's Proving Ground, so teams can confirm ROI and reliability before committing at scale — a modern alternative to legacy, static bots and fragmented support stacks.
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Archestra
Archestra is an open source, self-hosted AI platform for deploying and governing agents across an organization. It provides agentic chat for non-developers, apps and skills, shared projects, a server-side agent runtime, MCP orchestration, permission-aware RAG, LLM and MCP proxies, security guardrails, and observability in one platform. Users sign in with SSO, and every tool call runs under that person’s own identity rather than a shared service account. Projects keep chats, files, scheduled tasks, and instructions together, while agents run in sandboxed containers and can start from schedules, emails, or webhooks. MCP servers run in the organization’s own Kubernetes environment and move through security-reviewed promotion flows with separate credentials and network policies. Knowledge bases can connect Confluence, Jira, drives, and internal documents while preserving source-system ACLs, so users only retrieve content they are already allowed to access.
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