Commerce AI

Commerce AI's core product is auto-AGENTS™, an autonomous, self-improving AI agent system for contact centers. It is positioned as "not a bot, but a coordinated team," composed of multiple specialized agents that handle listening, reasoning, execution, resolution, measurement, and learning end to end across voice and chat channels, thereby replacing traditional call centers.

In terms of purpose, auto-AGENTS™ is designed to address highly repetitive work in contact centers, including customer inquiries, refund processing, account updates, troubleshooting, and escalation transfers. It emphasizes "real resolution, not deflection," and can read from and write to enterprise systems, taking action within policy boundaries.

Key capabilities include:

• Self-improving loop: runs a "resolve—measure—learn—optimize" loop on real traffic, automatically tuning prompts, routing, and TokenTrim™ compression. Post-call autoQA scores 100% of calls, winning patterns are automatically promoted, and every change is gated, measured, and rollback-capable.
• TokenTrim™: a token compression layer that in benchmark tests reduced LLM tokens per voice call from 98,938 to 9,465, about one tenth, with cost also about one tenth, and no noticeable accuracy loss.
• Voice-native: streaming voice, a low-latency orchestration layer, preconfigured model endpoints, an end-to-end speech-to-speech budget of about 500 milliseconds, and support for interruptions, fallbacks, and circuit breaking.
• Multichannel: the same agent shares memory, tools, and policies across voice, chat, in-app SDK, asynchronous messaging, and other channels, and conversations can continue across channels without losing context.
• Multilingual and voices: supports 119 languages and 535 voices, can clone custom voices, teach pronunciation of brand terminology, translate in real time during calls, and provides active noise cancellation and voice activity detection.
• API-first: every capability is a single API call and can be orchestrated from your own stack, with no UI lock-in; setting self_improve: true runs the loop on your own traffic.
• Integrations: 62 production integrations covering CRM, CCaaS, data, and telephony systems, with support for PSTN and SIP, and available on AWS and Azure marketplaces.
• Human assistance and transfer: when human takeover is needed, it can perform a warm transfer with full context, summaries, and suggested next steps, and continue to assist in real time by drafting replies, surfacing knowledge, and automatically filling out post-call work.
• Multi-agent orchestration: intent-based routing sends conversations to the right agents and tools, steps that can be parallelized are executed in parallel to reduce latency, and the entire workflowOrchestratable, observable, rollback-capable.
• Measurement and monitoring: autoQA scores resolution, compliance, sentiment, and tokens for every call, presents trends, and provides one-click recommendations.
• Deterministic guardrails: hard policy boundaries that models cannot cross, real-time compliance monitoring, sensitive data is redacted before reaching the model, and all operations are logged for audit.
• Change management: safely tune, version, and upgrade models, run regression tests against real conversations, promote through staging and release workflows, and simulate thousands of users before launch.
• No-engineer configuration: tone, guardrails, knowledge, routing, and more can all be managed by business personnel, with a complete test suite and multi-user QA support.
• Knowledge grounding: answers are retrieved from the enterprise's own knowledge, policies, and real-time systems, with sources attached, and a clean no-answer fallback is provided when it should not guess.
• Compliance and security: SOC 2, HIPAA, ISO 27001, PCI DSS, GDPR, as well as ISO 42001, ISO 27701, and EU AI Act alignment, AES-256 encryption at rest, TLS 1.3 encryption in transit, role-based access control, voice authentication, zero data retention training, and 24/7 SOC monitoring.
• High availability: regional redundancy, automatic failover, and full-system observability.
• Flexible deployment: cloud, on-premises, or designated regions, with support for US, EU, APAC, and Latin America data residency.

In terms of usage, users can run auto-AGENTS™ via API from their own orchestration layer, CCaaS, or backend, without a UI; they can also use its management interface to configure tone, guardrails, knowledge, and routing. The system provides a reference architecture, with benchmarking supporting 10,000 concurrent calls, 1.75x burst testing, p95 latency budgets, autoscaling, and graceful degradation.

Applicable scenarios include: enterprise contact centers, BPO and multi-brand operations (supporting multi-tenancy and white-labeling), regulated industries (finance, healthcare, etc.), and global customer service requiring multilingual support and regional data residency.

In terms of limitations, the materials do not provide detailed information on specific pricing, free trials, implementation timelines, or independent third-party performance validation. Some capabilities (such as 10,000 concurrency and 500 ms latency) are benchmark or reference architecture data, and actual performance may vary depending on the deployment environment.