We are Phinite. We build infrastructure for deploying production-ready multi-agent systems.
The problem: building multi-agent systems requires you to think
in graphs — nodes, edges, agent roles, tool connections, prompts.
Most engineers spend more time architecting the workflow than
actually solving the business problem.
So we built Phinite Aura — you describe what you want in plain
English, and it designs the full multi-agent workflow for you:
agents, prompts, tool connections, and the underlying code.
Example from our own testing:
"I want to build an e-commerce product comparison assistant"
Aura generated: an orchestrator agent, 3 parallel product data
extractor agents, a comparative analysis agent, connected tools
(scrapers, APIs), and all the prompts. In under 60 seconds.
You can then modify it conversationally — "add a third product" —
and it updates the entire workflow graph including agent logic,
variables, and connections.
The canvas is live, versioned, and deployable. Integrations
include Salesforce, Slack, GitHub, Google Sheets, Notion, and
23 others out of the box. Built-in dev/UAT/prod environments
with Kubernetes-isolated traffic.
We built this because we were frustrated watching engineering
teams spend weeks on workflow architecture before writing a
single line of business logic.
Happy to discuss the architecture, how Aura handles ambiguous
instructions, or where it still fails.
I'm Swapnil, and I've been building AI agents for the past year. After the 10th time setting up the same infrastructure (Kubernetes, LLM routing, secrets management, monitoring), my co-founder and I decided to build the platform we wished existed.
Phinite is a developer-first platform for building, deploying, and orchestrating AI agents.
*Core features:*
- FlowGen Studio: Visual workflow builder for agent orchestration (think n8n meets LangChain)
- Developer Studio: Full IDE for custom tools with AI copilot assistance
- One-click deployments to managed Kubernetes
- Multi-environment support (DEV/UAT/PROD) with secrets management
- 50+ pre-built integrations (Slack, JIRA, Salesforce, etc.)
- Built-in observability and cost tracking
*Technical architecture:*
- Cloud-agnostic (AWS, GCP, Azure, or on-prem K8s)
- Auto-scaling pod orchestration
- Microservices architecture with service mesh
- WebAssembly-based runtime for tool execution
- Vector DB integration for RAG workflows
*Why we built it:*
Most AI agent frameworks are either too low-level (write everything in Python) or too constrained (no-code boxes that break when you need custom logic). We wanted something that works for both the "I need this done in 5 minutes" and "I need full control" use cases.
*Pricing:*
- $10 free credits (no credit card)
- Pay-as-you-go: $20 base + usage-based pricing
- Self-hosted option coming soon
*What we're looking for:*
- Feedback on the developer experience
- Performance benchmarks vs. self-hosted solutions
- Use cases you'd build (or wouldn't build, and why)
- Technical deep-dives you'd like to see
We're currently in UAT with 100+ beta testers and opening to the public today.
We are Phinite. We build infrastructure for deploying production-ready multi-agent systems.
The problem: building multi-agent systems requires you to think in graphs — nodes, edges, agent roles, tool connections, prompts. Most engineers spend more time architecting the workflow than actually solving the business problem.
So we built Phinite Aura — you describe what you want in plain English, and it designs the full multi-agent workflow for you: agents, prompts, tool connections, and the underlying code.
Example from our own testing: "I want to build an e-commerce product comparison assistant"
Aura generated: an orchestrator agent, 3 parallel product data extractor agents, a comparative analysis agent, connected tools (scrapers, APIs), and all the prompts. In under 60 seconds.
You can then modify it conversationally — "add a third product" — and it updates the entire workflow graph including agent logic, variables, and connections.
The canvas is live, versioned, and deployable. Integrations include Salesforce, Slack, GitHub, Google Sheets, Notion, and 23 others out of the box. Built-in dev/UAT/prod environments with Kubernetes-isolated traffic.
We built this because we were frustrated watching engineering teams spend weeks on workflow architecture before writing a single line of business logic.
Happy to discuss the architecture, how Aura handles ambiguous instructions, or where it still fails.
Try it: www.phinite.ai