The Platform for AI
AI is a new layer of your business. Work that used to take teams now runs on instructions your people write. That layer needs a platform - not chat in one tool, prompts in docs, workflows in another.
Chat
Multi-model interface (ChatGPT, Claude, Gemini and more). Switch mid-conversation. Fork threads to test different approaches.
Prompts
Version controlled components. Deploy to chat, workflows, APIs. Build once, use everywhere.
Workflows
Chain components into automated processes. Add logic, human-in-the-loop steps, integrations.
Playgrounds
Test prompts across models side-by-side. Compare outputs before you deploy.
Why Aisle
- •Built for teams: What one person builds, everyone deploys. Work compounds across your organization.
- •Build once, use everywhere: Create a prompt. Deploy it in chat, workflows, and APIs.
- •Compounds: Prompts become building blocks. Blocks combine into workflows. Your capability grows.
- •Model-agnostic: Use OpenAI today, Anthropic tomorrow. Switch providers without rebuilding.
- •Your infrastructure: Your operational logic lives in systems you own, not vendor accounts you rent.
- •Future-proof: New models launch quarterly. Your platform grows with the ecosystem.
Ready to build AI infrastructure that compounds?
Own Your Infrastructure
AI is running real work now. Customer support. Document processing. Research. These are core operations and no longer experiments.
When you're replacing core processes, you can't be dependent on any single vendor. Your operational logic needs to be yours. Build on infrastructure you control, where your prompts and workflows work across any provider.
Build Future-Proof
GPT-4 was state of the art. Then Claude beat it. Then Gemini got cheaper. This will keep happening.
When your logic is abstracted from the model changes and upgrades are simple. When it's hardcoded, upgrades are rewrites. Build so that models are components, not foundations. Your operational logic, the actual business value, stays intact regardless of which vendor wins. This is how you build AI operations that last.
The Factory Approach
The bet on AI agents is a bet on autonomous systems that figure out your business. That's a gamble on timelines and intelligence you don't control.
The factory approach is different. It's a methodology for breaking down your business processes into manageable pieces. Each unit does one job. Test independently. Then chain units together into production lines. When something breaks, you know which unit. When something works, you reuse it. Units compound into sophisticated systems. Build momentum and Infrastructure while your competitors run failed experiments.