LLMs are powerful, but hard to manage. Everyone prompts, few can optimize.
We're building the bridge between human and AI collaboration with high power tools that are simple to use.
The next wave of productivity tools will be LLM-native, with memory, traceability, cost management, and seamless teamwork built in.
One workspace for research, drafts, revisions, and exports—across multiple AI models.
AI constantly forgets — even with giant context windows. Why should powerful intelligence require so much spoon-feeding?
LLMs now accept larger context sizes such as 1m but model attention limits are much smaller. Even the best models forget what happened a few minutes ago.
Bigger prompts = higher costs, lower speed. Token budgets constrain intelligent workflows.
Manually pasting prompts into two different chat programs. Spoon-feeding the AI. Repetitive, clerical, fragile, mindless.
Without a shared workspace, collaboration from human to AI and AI-to-AI is limited.
Your context and work are remembered and reusable. True collaboration with teammates and AI in real-time.
Prompt once, use many times
Teach those pesky LLMs to share memories
Forget when you are ready to forget.
Take control of your memories
Invite others to your chat thread
Share chat threads and chat history with teams
Compare responses from different AI agents
Chain from one LLM to another
Use low cost LLM for low cost prompts
Define reusable prompts for consistency and reliability
Built-in observability, multi-agent workflows, and true collaboration. Work smarter with AI that remembers and teammates who can contribute.
Complete transparency with history logs, prompts and results saved, and metrics. Track inputs, outputs, token usage, latency, and model versions.
Workflows with multiple specialized AI agents, agent-to-agent communication, and broadcast messages across agents.
Co-edit prompts or documents, AI joins the conversation, invite teammates to chat history, share agents and memories.
Your context and work are remembered and reusable. Share memories with more than one AI model. Take control of memory with asynchronous workflows.
Design, shape, and control AI interactions with precision. Build structured prompts, custom contexts, multi-model comparisons, and repeatable workflows without writing code.
