auto-AGENT runs simulated callers, applies safe instruction fixes, rebuilds the flow, and re-evaluates, recursively, until it passes.
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Fix saved to current flow. Continue to live tests, or run another.
Reviewer approved the suggested instruction changes.
Safe instruction fixes applied & flow rebuilt automatically.
auto-AGENTS™ isn't one bot, it's a coordinated team running your calls. One agent listens, another reasons, another acts on your systems. QA scores every call, and the whole contact center tunes itself, continuously.
We brought large language models to the contact center before ChatGPT existed. That head start compounded, into the most efficient engine in the category, a system that improves itself, and a full replacement for the old-school call center. Here is the whole story.
Before ChatGPT launched, auto-AGENTS™ was already resolving real conversations with large language models in production, while the market was still scripting decision trees. That head start is the moat behind every benchmark on this page.
Because we have run LLMs at scale longer than anyone, we engineered TokenTrim™, our token-compression layer. In benchmarking it cut LLM tokens per voice call from 98,938 to 9,465, about a tenth of the tokens, and a tenth of the cost. It keeps sharpening as the loop learns.
The product is built around a closed loop that runs on live traffic, resolve, measure, learn, optimize, automatically tuning prompts, routing and TokenTrim™ from real outcomes. Post-call autoQA scores 100% of calls; winning patterns are promoted automatically; every change is gated, measured and reversible.
Competitors ship a single assistant. auto-AGENTS™ is a coordinated system of specialized agents, listening, reasoning, acting, resolving, measuring and learning, that does the entire job of a contact center, end to end and within your policy.
Resolution rate climbs and cost per resolution falls, month over month, without you lifting a finger, the compounding payoff of the loop running on your real traffic.
Streaming speech, a low-latency orchestration tier, provisioned model endpoints and a measured speech-to-speech budget of about 500ms end to end. Barge-in, fallback and circuit breakers built in.
auto-AGENTS™ reads and writes to your systems, updating accounts, processing refunds, troubleshooting, escalating, all within policy. Real resolutions, not deflections.
A horizontally-scaled reference architecture benchmarked for high-concurrency voice, admission control, regional quota planning, autoscaling and burst testing at 1.75× steady state, validated for regulated workloads.
The same agent carries shared memory, tools and policy across every channel, so a conversation that starts on voice can continue on chat without losing context. Voice-first, with real barge-in and live hand-off.
Speak to every customer in their language and your tone. Clone a custom voice, teach branded-term pronunciation, translate live mid-call, and stay crisp on noisy lines with active noise suppression and voice-activity detection.
Every capability is a single API call, start a call, route, resolve, refund, escalate. Orchestrate auto-AGENTS™ from your own stack with no UI lock-in. Set self_improve: true and the loop runs on your traffic.
62 production integrations across the Fortune 500 stack, CRM, CCaaS, data and telephony, pulling context, personalising responses and taking action via API, connectors or MCP. PSTN & SIP native. Listed on AWS & Azure marketplaces.
When a human should take over, auto-AGENTS™ hands off warm, with full context, a summary and suggested next steps, and keeps assisting live: drafting replies, surfacing knowledge and auto-filling the after-call work.
Intent-based routing sends each conversation to the right agent and the right tools. Steps that can run together run in parallel to cut latency, and the whole workflow is orchestrated, observable and reversible.
autoQA grades resolution, compliance, sentiment and tokens on every call, surfacing emergent trends and one-click recommendations you can set live to immediately improve performance. Full audit and reporting, end to end.
Hard policy boundaries the model cannot cross, monitored for compliance in real time. Sensitive data is redacted before it ever reaches a model, and every action is logged for audit.
Tune models, version and upgrade them safely, run regression tests against real conversations, and promote through staging and release workflows. Simulate thousands of users before a single live call.
Every aspect of auto-AGENTS™ is designed to be managed by you: tone, guardrails, knowledge, routing. Experiment, simulate and ship changes with confidence using a full testing suite and multi-user QA support.
Answers are retrieved from your own knowledge, policies and live systems, with sources attached and a clean no-answer fallback when it should not guess. Knowledge stays in sync, so the agent is never out of date.
SOC 2, HIPAA, ISO 27001, PCI DSS and GDPR, plus ISO 42001, ISO 27701 and EU AI Act alignment, with AES-256, TLS 1.3, role-based access control, voice-based authentication, zero-data-retention training and 24/7 SOC monitoring.
Architected for high availability with regional redundancy, automatic failover and full system observability, so the agents stay up even when something underneath does not.
Run auto-AGENTS™ wherever your compliance team needs it, fully managed in the cloud, in your data-residency region, or on-prem behind your firewall. Same product, your boundary.
TokenTrim™ and the self-improving loop drive cost per resolution down every month while resolution and CSAT climb. Model your own numbers in seconds.
auto-AGENTS™ has influenced over a billion dollars in revenue across 1B+ conversations, for enterprises that put their hardest, most regulated workloads on it.
We were first to bring the LLM here, and we intend to define what comes next: a contact center that runs itself, learns from every conversation, and gets better while you sleep. That is the whole point of the name, auto-AGENTS™.
The lowest cost per resolution in the category, in every language and region your customers, and your clients, operate in.
TokenTrim™ cuts compute ~10×, driving the lowest cost per resolution.
535 voices, live translation and branded pronunciation for every market.
Cloud, on-prem or in-region, US, EU, APAC & LATAM data residency.
Multi-tenant & white-label, run many brands, expand margin per seat.
119 languages, 535 voices, barge-in and live hand-off.
In-app SDK and web chat with full memory.
Async messaging that continues across channels.
Long-form resolution with policy-aware actions.
Drive any channel from your own stack.
Automated QA and scoring on 100% of calls.
Start from the team you run today, see the labor cost freed as auto-AGENTS™ takes on repetitive volume.
Savings reflect the labor cost freed as agents are relieved of repetitive volume, before platform and usage fees. Estimates only.
auto-AGENTS™ runs a closed loop in production, resolve, measure, learn, optimize, automatically tuning prompts, routing and TokenTrim™ compression from real outcomes. Resolution trends up and per-resolution compute trends down over time, with every change measured, gated and reversible. Explore Recursive auto-AGENTS™ →
Most of a call's tokens are repeated context, instructions, history, retrieved docs, tool scaffolding. TokenTrim™ distills and compresses that footprint before it reaches the model, cutting tokens about 10× with no measurable accuracy loss. It works with our models or your own.
Every capability is an API. Run auto-AGENTS™ entirely from your own orchestration layer, CCaaS or backend with no required UI. Your agents call ours, and ours call your tools.
Yes, our reference architecture is benchmarked for 10,000 concurrent calls with 1.75× burst testing, p95 latency budgets, autoscaling and graceful degradation, validated for regulated workloads.
SOC 2 Type II, HIPAA, ISO 27001, PCI DSS and GDPR, plus ISO 42001, ISO 27701 and EU AI Act alignment, with AES-256 at rest, TLS 1.3 in transit, zero-data-retention training, 24/7 SOC monitoring and US/EU residency.
Deploy a voice agent that resolves end to end, then learns from every call and gets better every week.