InnoCoworker
An AI collaboration workspace for teams. Bring project discussions, source materials and knowledge together, and move work forward with a shared context.
Open InnoCoworkerStart with InnoCoworker, our latest and top recommendation for team AI collaboration. Alongside InnoAgent for personal learning and InnoSpark for model access, it forms our three core products.
Team collaboration, personal agents and model access — choose where to start.
An AI collaboration workspace for teams. Bring project discussions, source materials and knowledge together, and move work forward with a shared context.
Open InnoCoworkerAn AI collaboration workspace for teams. Bring project discussions, source materials and knowledge together, and move work forward with a shared context.
Organize members, projects and shared materials in dedicated spaces.
Collect project materials, organize knowledge and return to the original sources.
Connect group discussions and project context through Feishu / Lark collaboration.
Reasoning, fast interaction, multimodal work and embedding do not need the same model. InnoSpark gives teams a visible place to compare available models and choose by task.
Use one service surface to discover models for generation, reasoning and retrieval instead of binding every product decision to one vendor.
Start from visible model and usage information. Shanghai Seii.top Technology is extending this foundation into practical token access and service support.
Connect agent applications through OpenAI- or Anthropic-compatible provider configuration and keep model choice replaceable.
InnoAgent organizes learner profile, knowledge Wiki, session recall, proactive review and hands-on practice into one long-running learning loop. It can run locally and connect to replaceable model providers.
Goals, knowledge state, misconceptions and preferences stay visible, correctable and evidence-based.
PDF, Office, image and text sources become maintainable pages with traceable origins and graph relationships.
Recent conversations and tool traces support continuity without mixing temporary chat into long-term knowledge.
Reviews, profile reflection, knowledge updates and custom tasks can move learning forward on a schedule.
Generate exercises, run them in the workspace and continue from real output and errors in the next turn.
Desktop, Web and terminal modes share local runtime state while provider configuration keeps models replaceable.
Shanghai Seii.top Technology connects the parts that teams otherwise have to assemble alone.
Agent-native product, project and QA management with traceable records and evidence-based status.
02Transform internal material into reviewable professional documents while preserving facts and checking disclosure risk.
03Capture, organize and retain owned knowledge through web, desktop and Git-backed workflows.
Start with InnoCoworker, explore InnoAgent or choose models through InnoSpark.