RAGFlow vs Spanlens

RAGFlow and Spanlens are both inference engines & infra tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

RAGFlow

Open-source RAG engine with deep document understanding, hybrid search, and agentic workflow orchestration.

Spanlens

Spanlens sits in front of your LLM provider via a single baseURL change, recording every call's cost, latency, tokens, and full request-response body with no SDK rewrite required. Agent runs surface as waterfall span trees so you can identify the one step consuming 80% of wall-clock time. The model recommender flags GPT-4o calls that look like classification tasks and shows the cost delta if you swap — with numbers from your own traffic, not benchmarks. The eval and experiment layer lets you replay a fixed dataset across prompt versions before you ship, so quality regressions don't surprise you in production. PII scanning and anomaly detection run at log time, which matters when sensitive data crosses the wire at 3 a.m. with nobody watching.

Attribute	RAGFlow	Spanlens
Pricing	Paid	Paid
Price	$29/mo	$29/mo
Free trial	No	No
Open source	Yes	Yes
Has API	Yes	Yes
Self-hosted option	Yes	Yes
Platforms	Docker, Kubernetes, Linux, macOS, cloud (cloud.ragflow.io)	Node.js, Python, Next.js, Edge, self-hosted
Released	2024-04	—
Pros	Deep document understanding and structure recognition reduce noise and hallucinations Unified agentic platform—RAG, tools, and MCPs in one orchestration layer Fully open source, self-hostable, and enterprise-ready deployment options Rich visual UI with workflow builder, citation tracking, and chunking visualization Active community and rapid iteration; frequent feature and model updates	Proxy-layer instrumentation via a single baseURL change, so existing code requires no structural rewrite and every provider call is captured from day one rather than after a manual instrumentation sprint. Per-user and per-route cost attribution, which means you can identify the specific customer or endpoint burning disproportionate budget before it compounds across a billing cycle. Agent waterfall trace trees with critical-path highlighting, so a slow or expensive step in a multi-agent run is pinpointed in seconds instead of reproduced manually in a staging environment. Experiment runner replays a fixed dataset across prompt versions and models with quality, cost, and latency compared side by side, which means you ship with evidence that v8 is better than v7 rather than finding out the hard way in production. Self-hosted deployment via Docker Compose under MIT license, so teams with data residency or audit requirements can run the full platform without sending trace data to a third-party cloud.
Cons	Complex stack requiring Docker, Elasticsearch or Infinity, MySQL, MinIO, Redis—steep DevOps overhead Slower time-to-value for prototyping compared to managed SaaS alternatives Documentation and community libraries smaller than mature frameworks like LangChain	PII detection is regex-based and runs at log time as a flag — not a pre-storage redaction guarantee. Teams operating under HIPAA or SOC 2 controls where sensitive data must never reach a log store, even briefly, need a dedicated redaction layer upstream of Spanlens or a different architecture entirely. The LLM-as-judge eval scoring is a single 0–1 scalar per response. Teams needing structured, multi-criteria evaluation rubrics — for example, factual accuracy scored separately from tone and policy compliance — hit the ceiling of what the built-in scorer expresses and end up maintaining a custom eval harness alongside Spanlens. At high request volumes where the proxy layer adds measurable latency to every call, teams running latency-sensitive production paths at scale have moved to SDK-side instrumentation tools or full APM platforms with LLM plugins, where the observability path is out of band rather than in the critical path.

Bottom line

RAGFlow and Spanlens are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between RAGFlow and Spanlens?

RAGFlow is Paid and open source, while Spanlens is Paid and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is RAGFlow better than Spanlens?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.