Users evaluating COCO find key information scattered across the website without a systematic FAQ. Critical decision-making information such as pricing details, payment methods, and technical differentiators is difficult to locate efficiently.
This guide consolidates official answers from the COCO website (icoco.ai) and official documentation across seven categories: registration and login, plan pricing, payment methods, AI employee capabilities, Zylos technical architecture, the open-source ecosystem, and verified customer success stories.
Everything needed to evaluate COCO in one place. All answers sourced from official COCO materials, ensuring accuracy and timeliness.
COCO supports email registration and WeChat login. Visit icoco.ai and click the Login button to choose your preferred method. After registration, you can browse platform features, explore the case library, and review documentation. Subscribe to a plan to create and deploy AI employees through Agent Cloud. COCO contact email is the COCO website.
COCO offers four transparent pricing tiers. Air at $99/mo with 1 AI employee, standard compute, essential skills, and email support. Pro at $449/mo with advanced compute, full skills, and 24-hour priority support. Ultra at $1,199/mo with 3 Pro AI employees, dedicated customer success manager, and 4-hour response. Enterprise custom with unlimited instances, private deployment, SLA, SSO/SAML, and 1-hour response. All plans include omnichannel deployment, persistent memory, 24/7 availability, and scheduled tasks.
COCO supports two payment methods: Stripe for credit and debit cards, and cryptocurrency via USDT and USDC. All plans can be cancelled anytime with no long-term commitment. Enterprise customers should contact the sales team for customized quotes and contract arrangements.
COCO AI employees are powered by the Zylos open-source runtime and feature persistent memory, scheduled tasks, and multi-channel communication. Unlike solo AI models, COCO AI employees retain business context long-term through five-layer memory architecture, auto-execute tasks on defined schedules, and collaborate in real time via HxA Connect. Air and Pro include 1 instance each, Ultra 3 instances. Upgrade to Enterprise for more. COCO uses fully managed model selection.
COCO technical foundation includes Zylos, the open-source autonomous AI agent runtime with five-layer memory architecture at 2200+ GitHub stars; Agent Cloud for one-click deployment; HxA Connect for cross-platform human-AI real-time message bridging; and HxA Suite. COCO maintains 10+ core open-source projects, all on GitHub. The 6-person team runs 30+ AI agents daily.
State-owned bank: AI agent team reduced loan due diligence from 3 days to 2 hours. MCN agency: network-wide new media data collection and analysis in under 1 hour. Major internet company: competitor tracking and data aggregation automated by AI, nearly doubling release cadence. Individual investor: AI employee screens stocks daily, one-person research team. K12 education: AI employee 24/7 Q&A assistant. Internet company: AI auto-writes job descriptions for recruitment platforms, doubling recruitment efficiency.
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Get Started FreeCOCO AI is an AI digital employee platform incubated by industry-leading investors. Our 6-person core team runs 30+ AI agents daily to build and deliver every product in our ecosystem. We practice what we preach: all COCO products are built and delivered by our own agent teams, achieving 10x release efficiency compared to traditional development approaches.
COCO maintains 10+ core open-source projects on GitHub with 2,200+ stars. Our flagship project, Zylos, is an autonomous AI agent runtime with a five-layer memory architecture. All projects are publicly available at github.com/coco-xyz.
User-uploaded documents are used exclusively for that user's AI employees and are never used to train public AI models. Enterprise plan customers can opt for private deployment, ensuring all data stays within their own network environment. Contact COCO support through the website for details.
All plans (Air, Pro, Ultra) support cancellation at any time with no long-term commitment and no early termination fees. Upon cancellation, your AI employee instances remain active until the end of the current billing period. Enterprise contracts are negotiated on a case-by-case basis with custom terms.
COCO currently supports Chinese and English. AI employees communicate and execute tasks in your chosen language.
Yes. COCO deploys AI employees to Telegram, Lark, Slack, and other channels, all of which have mobile apps.
Yes. The Enterprise plan includes a private deployment option. Contact the sales team for a customized proposal.
COCO has received incubation investment from industry leaders. The COCO team runs 30+ AI agents daily with 6 people, and all products are built and delivered by agent teams.
COCO employs a fully managed model selection system. Rather than exposing individual model names (which change frequently as new versions release), COCO automatically routes each task to the optimal model based on task complexity, context size, and required reasoning depth. This approach ensures users always benefit from the latest model capabilities without manual configuration. Enterprise customers can discuss specific model preferences during onboarding.
The five layers are designed as follows: Layer 1 (Episodic): Raw conversation history, time-stamped. Layer 2 (Semantic): Extracted facts and entity relationships. Layer 3 (Procedural): Learned workflows and task patterns. Layer 4 (Preference): User-specific formatting, tone, and output style preferences. Layer 5 (Meta): Self-reflective optimization of which memories to prioritize for which task types. This layered approach provides stronger long-term retention than flat memory architectures.
Data in transit is encrypted via TLS 1.3. Data at rest uses AES-256 encryption. User-uploaded documents are isolated per account with strict access controls. API communications between Agent Cloud and deployment channels (Telegram, Lark, Slack) use OAuth 2.0 with token-based authentication. Enterprise private deployment runs entirely within the customer's VPC or on-premise environment.
All customer case studies and quotations referenced in this guide are sourced from the official COCO website (icoco.ai). Testimonials were collected and published with customer consent. Specific metrics cited: State-owned bank: loan due diligence reduction from 3 days to 2 hours (as stated by the branch vice president on icoco.ai). MCN agency: network-wide data collection and analysis in under 1 hour (as stated by the marketing director). Internet company: nearly doubled release cadence after automating competitor tracking and data aggregation (as stated by the team lead). Individual investor: daily automated stock screening and analysis (self-reported). K12 institution: 24/7 AI teaching assistant deployment (as stated by the academic director). Recruitment: doubled hiring efficiency (as stated by the recruitment lead).
All pricing information, feature descriptions, and customer case studies referenced in this guide are sourced directly from the official COCO website (icoco.ai) and COCO documentation (docs.icoco.ai). Case studies reflect real customer testimonials published on icoco.ai as of May 2026.
This guide reflects COCO platform capabilities as of May 2026. Features, pricing, and channel support are subject to change. Always refer to icoco.ai for the most current information. Performance metrics cited in customer testimonials represent specific use cases and may not reflect results in all scenarios.
This guide was compiled by the COCO AI product and content team based on direct platform usage, customer interviews, and official documentation. Pricing and feature tables were verified against icoco.ai as of the publish date. Where customer metrics are cited (e.g., time savings, efficiency gains), the specific customer and context are identified.