Who Should Use Feluda?

You already use AI — pasting data into ChatGPT, copying the output into a spreadsheet, switching to another tool for a second opinion, then formatting it all for a stakeholder. Feluda replaces that entire cycle with a single visual workflow you build once and reuse forever.

Common use cases: email triage and classification, daily report generation, data extraction from documents, meeting-summary formatting, and invoice processing. Build the flow in Studio, schedule it with the Schedule Manager, and review results in the Journal.

Why Feluda, not a cloud tool? Your business data stays on your machine. API keys are encrypted in your OS vault. You can run flows on a schedule without paying per-execution cloud fees. And you do not need IT support to set it up.

Content production involves many AI steps: draft a blog post, generate social media posts, classify the tone, create a featured image. Today, that means switching between tools and copying output back and forth. In Feluda, you connect all those steps into one pipeline.

Common use cases: blog-to-social content pipelines, tone and style classification, image generation from text briefs, translation workflows, and SEO-optimised content generation. One input brief produces a complete content package in a single execution.

Why Feluda? You build the pipeline once and run it for every project. Compare outputs from different AI providers side-by-side in the Workbench. No coding, no copy-paste, no per-execution fees for local models.

Research demands reproducibility. If you run an analysis today, you need to be able to explain exactly what model was used, what prompt was sent, and what data went in. Most AI tools offer none of this. Feluda logs every prompt, response, tool call, and configuration change automatically.

Common use cases: structured data extraction from unstructured reports, multi-provider model comparison (quality, speed, cost), literature classification and labelling, PII detection and redaction before sharing datasets, and automated journal entries during scheduled analysis runs.

Why Feluda? Full audit trail for every AI interaction. Local AI models mean sensitive research data never leaves your machine. The free plan gives you full access to Studio, Workbench, and RunFlows — enough to run serious analysis pipelines at zero cost.

Feluda was built by cybersecurity veterans. It includes tools for port scanning, domain lookups, and network reconnaissance — combined with AI that interprets results and writes human-readable reports. Schedule these flows to run weekly and review findings in the Journal.

Common use cases: automated infrastructure scanning on a weekly cadence, domain intelligence and WHOIS lookups, threat-assessment report generation, vulnerability summary pipelines, and PII detection across internal documents.

Why Feluda? Every action is logged. Secrets are encrypted in your OS vault — the AI never sees them. Flows handle errors gracefully with typed error outputs (rate limit, timeout, content filter). And you can run everything offline with local models when cloud access is not appropriate.

Developers get the visual builder like everyone else — but they also get Feluda's built-in MCP server (Model Context Protocol). This connects Feluda to your IDE — VS Code, Cursor, and any MCP-compatible editor — so your AI coding assistant can use Feluda's tools, prompts, and workflows directly from your development environment.

Common use cases: rapid AI workflow prototyping without writing API glue code, MCP server for IDE integration, building and testing custom Genes (automation packages), comparing model performance across providers, and debugging AI pipelines with the Activity log.

Why Feluda? Skip the boilerplate. Prototype AI workflows visually in Studio, test them in the Workbench, then use them from your IDE via MCP. API keys are managed securely — no .env files. Visit the Developers Hub for integration details.

When your organisation handles regulated, classified, or personally identifiable data, cloud-only AI tools are off the table. Feluda runs on your desktop. It supports fully local AI models. Secrets are encrypted in your OS vault. And every prompt, response, and tool call is logged automatically — providing the audit trail compliance teams need.

Common use cases: GDPR-compliant document processing, PII detection and redaction before external sharing, auditable AI decision pipelines, organisation-wide deployment of standardised Genes, and secure multi-provider orchestration without data leaving the network.

Why Feluda? Feluda Enterprise offers centralised management, shared Genes across teams, and enterprise-grade governance. The desktop-first architecture means data stays where your compliance framework says it should. Read the Threat Intelligence case study for a real-world example.

You want to experiment with AI — test different models, build personal assistants, compare how OpenAI and Anthropic handle the same prompt, or see what a local model can do on your own hardware. Feluda makes all of this possible without writing a single line of code.

Common use cases: comparing AI model outputs in the Workbench, building personal AI assistants with real tool access (web search, file operations, journal writing), prototyping workflow ideas visually, and exploring local AI models through Ollama or LM Studio.

Why Feluda? The free plan gives you full access to Studio, Workbench, RunFlows, the Journal, and the built-in MCP server. Local models run at zero cost. You can explore, learn, and build — at your own pace, on your own machine.