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CX Today named Aissist.io the Most Innovative CX Technology of 2026 in its CX Today Awards, recognizing its AI agent platform for customer experience.
See the winnersAissist.io introduced the Universal Connector, one way to connect AI agents to the systems a business already runs on. It supports 32 types of connection, including Google Drive, Microsoft OneDrive, databases, Slack, and more, so agents can read the knowledge and data they need, and take action, without a custom integration for each system.
Explore integrationsAissist.io introduced the Ask Engine, part of Pulse, which lets a team question its operation in plain language the way it would ask an analyst: about a product, a customer segment, an operation, or a single agent. Answers come back in seconds, drawn from the full conversation record rather than a sample, and say what the evidence does not support instead of guessing at a cause. It turns reporting into investigation: not just that resolution dropped overnight, but where, why, and when.
Explore the Ask EngineAissist.io released the alpha version of self-evolve AI, the closed loop that wires execution, evaluation, and optimization into one system: AgentMesh does the work, Pulse evaluates every conversation against the business's own standard, and Evolve diagnoses the gaps, runs experiments, and ships what works. The alpha moves continuous improvement from a manual review cycle into an architecture that learns from the traffic it already handles.
Explore self-evolve AIAissist.io launched the beta of Agent Insight, which measures and tracks the performance of every agent in an operation — AI and human — against the same standard, using metrics each business defines. The beta turns AI evaluation from a black box into a transparent scorecard: how good the AI is, how it compares with the team, whether it complies with the QA guideline, and what to improve next.
Explore Agent InsightCIOReview named Aissist.io the Best Agentic AI for Business, recognizing AgentMesh for coordinating specialized agents to resolve complex support and sales work end to end rather than simply deflecting tickets. The recognition highlights Aissist.io's measurable outcomes — high resolution rates, strong CSAT, and cost well below traditional alternatives.
Read the original articleAissist.io published the AI Customer Service Benchmark 2026, covering resolution rate, CSAT, and cost per resolution across six industries, with each vendor's published figure linked to its source. The benchmark sets out how each metric is defined and measured — resolution versus deflection above all — so buyers can compare deployments on a shared yardstick instead of a single headline number.
Read the benchmarkUSA Today featured Lifan Xu in a piece about how leadership is evolving as AI becomes more embedded in business operations. The article centers on the shift from traditional people management toward strategic AI fluency, data interpretation, and operational transformation.
Read the original articleAissist.io announced the product vision of Evolve as the engine for continuous optimization inside the AI Operational Layer. The vision positioned Evolve as the layer that helps identify gaps, detect opportunities, investigate signals, and improve operations over time rather than treating optimization as a separate manual process.
Explore EvolveInternational Business Times covered Lifan Xu's perspective on why enterprise AI efforts often fail to produce measurable ROI. The piece focuses on execution gaps, undefined success metrics, integration complexity, and the need to treat AI deployment as an operational discipline rather than a demo-stage experiment.
Read the original articleAissist.io launched the AI Operational Layer for Salesforce and Kustomer to help businesses unify automation, insight, and continuous optimization inside core enterprise and support systems. The rollout positioned operational AI as a closed loop that can execute work, generate intelligence, and improve workflows over time rather than functioning as isolated assistant tooling.
Explore AI Operational LayerAissist.io launched Pulse as the official product for insights across customers, agents, products, and operations as part of the AI Operational Layer. Many of those capabilities already existed in the platform, but the launch grouped them into one named product so businesses could treat operational intelligence as a first-class layer rather than a loose set of supporting features.
Explore PulseAissist.io introduced the vision for the AI Operational Layer as a closed loop that brings automation, insight, and continuous optimization together in one operating model. The position is that this represents a broader transformation in how businesses will run operations, moving from isolated AI assistance toward systems that can execute work, generate intelligence, and improve continuously over time.
Explore AI Operational LayerPRNewswire carried Aissist.io's launch coverage for its Hybrid AI Workforce, outlining the company's approach to moving AI from pilot-stage experimentation into governed, production-ready operations. The release emphasizes end-to-end automation, operational visibility, and measurable business impact.
Read the original articleAissist.io officially introduced the product name AgentMesh for its automation offering built on top of the Multi-Agent Platform. The naming clarified AgentMesh as the execution layer designed to help businesses automate support and sales end to end through coordinated agents rather than assistant-style drafting alone.
Explore AgentMeshAissist.io expanded the Multi-Agent Platform across Freshdesk and Zendesk to help businesses automate customer service inside two widely used support platforms. The rollout focused on moving beyond copilot-style assistance toward agents that can coordinate tasks, take actions, and drive cases toward resolution across real operational workflows.
Explore Multi-Agent PlatformAissist.io launched the Multi-Agent Platform on Intercom to help businesses automate support and sales with coordinated AI agents instead of isolated drafting tools. The rollout reinforced the idea that business AI should execute real operational work end to end inside the systems teams already use.
Explore Multi-Agent PlatformAissist.io expanded the Multi-Agent Platform across FrontApp and Gorgias to help businesses automate sales and support inside real team workflows and commerce support environments. The rollout emphasized multi-agent coordination for operational work that requires reasoning, context, product knowledge, and system actions beyond simple drafting.
Explore Multi-Agent Platform