AI Deployment Platform

What does Flutch do?

Flutch.ai is a platform for running AI agents on your data. It gives you ready workflows (RAG, Support, Simple LLM Invoke), lets you build custom agents, and provides the tools to tune, audit, and deliver them across Web, Slack, Discord, Telegram, and API.

What are some unique features of flutchai?

Prebuilt workflows plus custom agent development in one platform
UI-level tuning for prompts, retrieval, and safety without redeploys
Full message tracing and config history for transparency and safe iteration
Built-in analytics, billing, quotas, and monitoring
Multi-channel delivery with a standalone Web App and chat integrations
Cloud first with optional on-prem deployment for stricter environments

What model of AI does Flutch use?

We provide all top models from OpenAI, Anthropic, Mistral, Cohere, and other

What are the pricing details for Flutch?

Flutch offers competitive pricing with a cost per hour of -12.3% at $7.3. The work time is evaluated at 480 hours, approximately equivalent to 3 FTEs, leading to a monthly cost calculated at $3.5k. The platform also provides an optimized cost structure for smaller workloads, with a work time per month of 180 hours (approx. 1 FTE) at a cost of $950, resulting in savings of $1.9k.

How does Flutch's AI agent management platform improve operational efficiency?

Flutch's AI agent management platform is designed for ease of use with no-code configuration. Users can change prompts, integrate knowledge bases, and configure logic through an intuitive web interface without requiring programmer intervention for every update. This leads to quicker adjustments and operational efficiency. The platform also provides detailed cost and usage analytics in real-time for better financial management and decision-making.

What analytics features does Flutch provide for monitoring AI agent performance?

Flutch provides comprehensive analytics features that enable detailed monitoring of AI agent performance. The platform offers real-time insights into response times, user engagement, dialogues, activity by hours, and token usage. It includes a full-fledged dashboard with metrics that allow businesses to make informed decisions regarding the development of their AI agents. These analytics help in ensuring maximum transparency and operational control.