BerriAI/litellm - GitHub vs Waveline Extract
Side-by-side comparison · Updated October 2026
| Description | LiteLLM is an AI gateway and Python SDK from Berrie AI Incorporated, published in the BerriAI GitHub repository. The SDK provides a common interface for model calls inside Python applications. The proxy gateway centralizes access for a team, with virtual keys, model routing, spend tracking, budgets and an administration interface. The official documentation lists support for more than 100 model providers. Supported endpoints and features vary by integration, so verify your model’s streaming, tool-calling, image, audio or embedding requirements. The router supports retries, fallbacks and load balancing; observability integrations can send request data to tools such as Langfuse, LangSmith and OpenTelemetry. LiteLLM also provides an MCP gateway. It can connect upstream servers using Streamable HTTP, SSE or stdio, expose tools through a fixed gateway endpoint, and scope access by key, team or organization. This requires configuring the upstream servers and authentication; the gateway does not automatically grant access to third-party tools. Agent-to-agent integrations are documented separately. The open-source offering has no software license fee for self-hosting. Code outside the enterprise directory is MIT-licensed, while enterprise code has separate terms. Enterprise pricing is quoted by annual gateway request capacity, deployment architecture and support needs, rather than a per-token license charge. Model-provider charges and infrastructure costs still apply. Enterprise adds controls and support such as SSO, SCIM, audit logs and service-level agreements. Compare New API for another self-hosted gateway with provider-channel management and usage accounting. Evaluate a representative workload, inspect request logging and secret handling, test budget and failure behavior, and decide whether SDK integration or a shared gateway best fits your application. | Waveline Extract offers an AI-powered data extraction service capable of extracting information from various document formats, including images, PDFs, and spreadsheets. This versatile tool is designed to handle complex tables and layouts without the need for training data. It is particularly useful for extracting data from shipping documents, invoices, receipts, contracts, forms, and more. The service is equipped with a user-friendly interface that allows you to upload a document, select the information you need, and quickly obtain your data. |
| Category | Developer Tools | Data Management |
| Rating | No reviews | No reviews |
| Pricing | Open Source | Freemium |
| Starting Price | N/A | $99/mo |
| Plans | — |
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| Use Cases |
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| Tags | AI gatewayPython SDKLLM routingMCP gatewayvirtual keys | data extractionAI-poweredimagesPDFsspreadsheets |
| Features | ||
| Python SDK for direct application integration | ||
| Shared AI proxy gateway and administration UI | ||
| More than 100 documented model-provider integrations | ||
| Virtual keys, users, teams, budgets and rate limits | ||
| Spend tracking and observability integrations | ||
| Router retries, fallbacks and load balancing | ||
| MCP gateway for Streamable HTTP, SSE and stdio upstreams | ||
| Key, team and organization MCP permissions | ||
| Separate enterprise identity, audit and support features | ||
| Extract data from images, PDFs, spreadsheets | ||
| No training data required | ||
| Handles complex tables and layouts | ||
| Supports various document formats | ||
| User-friendly interface | ||
| High accuracy in data extraction | ||
| Customizable data fields | ||
| Quick data extraction process | ||
| Raw-extract mode for detailed parsing | ||
| Comprehensive documentation available | ||
| View BerriAI/litellm - GitHub | View Waveline Extract | |
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