AgentBull @AgentBullLab
AgentBull is a Neolab that builds intelligence amplifiers for key decision-makers through outcome-oriented AI agents. agentbull.com Singapore Joined September 2026-
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We’re Ankole, an early-stage open-source agent-first work environment. We’re not widely adopted yet, so I won’t pretend to be the battle-tested option you’re looking for. What we’re building: agents run complete tasks with state that persists across sessions, and output stays reusable as Pages/tables/reports instead of only chat. If you’re interested, feel free to check out our product.
Ankole 2.0 is here in its first alpha preview 🐂 v2.0.0-alpha.1 fundamentally redesigns how agents own computers, persistent storage, and workspace lifecycles. 5 shifts worth knowing about: • Dedicated Agent Computers: Workers now run unprivileged as uid 1000 with persistent /workspace across Docker, K8s, Cloudflare Containers, Lambda MicroVMs, and Function Compute. • Control Plane Drive: Each agent gets its own file drive (ankole-files). Manage skills, attachments, and scripts directly without spinning up a worker. • Multi-Tenant Isolation: Complete operator-managed tenant boundaries for people, agents, Brain memory, and channel credentials. • On-Demand Worker Lifecycle: The core agent loop now lives in the Elixir control plane. Pure questions need no worker; compute is acquired strictly when tools demand it. Full release notes & migration steps: github.com/AgentBull/anko…
Ankole is the open source alternative to Claude Tag: agents that sit in your team’s channels, remember every decision in a Company Brain, and keep working through a server restart.
Being accessible through Slack doesn't make an agent an AI coworker. If it only replies when tagged, it's an interface — not a workplace. Real work needs a runtime, persistent task state, tools, permissions, and a deliverable at the end. Slack is an inbox. Ankole is the workstation. github.com/AgentBull/anko…
Meet Bongard, the first open intuition model built on an encoder–decoder. It reads the whole situation at once and returns a calibrated probability for every option, in 36 ms, for about $4.40 per million decisions. 78% on DecisionBench, ahead of Jev. huggingface.co/AgentBull/bong…
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