Is Vesh Agents an open-source project?

Yes, Vesh Agents is an Apache 2.0 licensed open-source framework, providing full transparency, extensibility, and community contributions for its agentic AI capabilities.

Vesh Agents is an open-source agentic AI framework designed for comprehensive business data analysis, specifically focusing on revenue intelligence using a pipeline of 6 specialized AI agents.

Can I use my preferred LLM with Vesh Agents?

Yes, Vesh Agents supports Bring Your Own Model (BYOM), allowing you to integrate any LiteLLM-compatible Large Language Model (LLM) like Claude, GPT, or Llama.

What data sources can Vesh Agents connect to?

Vesh Agents can extract and analyze data from various sources including CSV files, Stripe, and Postgres databases, featuring automated entity resolution across these platforms.

Which SaaS metrics can Vesh Agents compute?

Out-of-the-box, Vesh Agents computes 10 key SaaS metrics such as MRR, New MRR, Expansion MRR, Churn, NRR, ARPU, Active Customers, Quick Ratio, and Logo Churn Rate.

Vesh Agents

Name: Vesh Agents
Author: shailesht003

byshailesht003

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Analytics & Monitoring

Developer Tools

Data Science & ML

Empowers businesses with an open-source agentic AI framework for comprehensive revenue intelligence and data analysis.

Vesh Agents is an innovative open-source agentic AI framework designed for sophisticated business data analysis, with an initial focus on SaaS revenue intelligence. Built on the OpenAI Agents SDK, it orchestrates 6 specialized AI agents into a pipeline that extracts, resolves, computes, detects, and explains your critical business data. Users can leverage their preferred LLM through BYOM (Bring Your Own Model) compatibility and integrate with various data sources like Stripe, Postgres, and CSVs, enabling deep insights into metrics like MRR, churn, and ARPU, alongside anomaly detection and root cause explanations.

Key Features

01Bring Your Own Model (BYOM) support for various LiteLLM-compatible LLMs

02Automated entity resolution across multiple data sources (CSV, Stripe, Postgres)

03Out-of-the-box computation for 10 key SaaS metrics (MRR, Churn, ARPU, NRR, etc.)

04Orchestrated pipeline of 6 specialized AI agents for business data analysis

050 GitHub stars

06Anomaly detection capabilities to identify unusual patterns in business metrics

Use Cases

01Analyze revenue and identify reasons for churn from CSV files, Stripe, or Postgres databases

02Automate daily pipelines for insights, anomaly alerts, and cross-company benchmarking

03Integrate AI-powered business data analysis into developer workflows via CLI or Python library