AI search, RAG and agents all depend on fast, relevant retrieval. These free tools help you size a vector search engine, tune hybrid search, model agent reliability and cost the clusters underneath, whether you run Elasticsearch, OpenSearch, Qdrant, Vespa or turbopuffer.
Estimate vector index memory for Elasticsearch, OpenSearch and Qdrant side by side, for any vector count, dimension and quantization - with the documented formula behind every number.
Edit keyword and vector result lists, switch between RRF and score normalization, and watch the fused ranking change. Copy the matching Elasticsearch or OpenSearch query.
Model an AI agent step by step - success rate, retries, verifiers, tokens - and see end-to-end reliability, cost and latency before you build.
Estimate Elasticsearch or OpenSearch storage and compute costs from published sizing guidance, with every unit price editable and sourced.
Assess your cluster health in 5 minutes. Get a detailed report on performance, reliability, security, and actionable recommendations.
32 essential best practices for production Elasticsearch. Interactive checklist covering performance, reliability, security, architecture, and monitoring.
Building with vector search, RAG or agents usually runs in the same order: choose and size the engine, tune retrieval, plan the agent, then run it well. Start where you are.
Vector search memory is driven by vector count, dimensions and quantization, so size it before you pick an engine. The vector sizing calculator compares Elasticsearch, OpenSearch and Qdrant side by side, and the comparison pages cover Vespa and turbopuffer trade-offs.
Hybrid search combines keyword and vector results, and the way you fuse their scores changes the ranking. The playground lets you test reciprocal rank fusion (RRF) against score normalization on your own result lists before you change a production query.
An agent that is right 95% of the time on each step finishes a 10-step task correctly only about 60% of the time. The agent reliability calculator models retries, verifiers, cost and latency so you can find the weakest step before you build.
Retrieval quality depends on a healthy, right-sized cluster. Estimate Elasticsearch or OpenSearch storage and compute costs, score your cluster in a five-minute health check, and work through the production checklist.
Side-by-side technical comparisons to help you pick the right retrieval engine for your product.
Created by the engineers who design, tune and operate search clusters for our clients.
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Vector search finds results by meaning instead of exact words. Text, images or other data are converted into embeddings, which are lists of numbers, and the engine returns the items whose embeddings are closest to the query. It is the retrieval step behind most RAG systems and AI agents.
Hybrid search runs a keyword query and a vector query together and merges the two ranked lists into one. Keyword search is strong on exact terms such as product codes and names, while vector search handles paraphrases and intent. The merge uses either reciprocal rank fusion (RRF) or score normalization, and the hybrid search playground shows how each one changes the order.
Raw float32 vectors take 4 bytes per dimension, so one million 768-dimension vectors need about 3 GB before any index overhead. Graph indexes such as HNSW add more on top, and quantization can cut the total. The vector sizing calculator shows the formula and the official documentation behind every number.
It depends on your data and your team. If you already run Elasticsearch or OpenSearch for keyword search and filters, adding vectors there is often the simplest path. Dedicated engines such as Qdrant, Vespa and turbopuffer fit other shapes of workload. Our comparison pages set out the trade-offs, and we recommend what fits your data, team and budget.
Reliability multiplies across steps. An agent that succeeds 95% of the time per step completes a 10-step task about 60% of the time. Retries, verification steps and fewer, better-designed tool calls raise that number, and the agent reliability calculator lets you test each change.
Yes. Every tool and checklist on this page is free, with no signup. Prices and assumptions in the calculators are editable, and results can be shared with a link.
Our tools give you a starting point. For your specific AI, agent or search challenge, book a free 30-minute call with our engineers.
