Cadenya vs Olostep: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Cadenya and Olostep — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Cadenya

Paid

A managed agent runtime that layers your tools, agents and objectives so teams can test agent behavior safely and iterate fast.

Unified Tool Layer: Connect MCP servers, OpenAPI specs and existing endpoints once, and expose them to every agent through a single managed interface.
Model-Agnostic Variations: Set a default model and run canary variations on other providers side by side to compare behaviors before promoting a change.
Progressive Tool Discovery: Tool schemas stay out of the context window until an agent asks for them, with configurable max tools per search, search hints and a rerank threshold, so every request gets smaller.
Live Token Metering: Track cost as it accrues across loops, active variations, memory entries and widgets, so usage is visible rather than discovered on the invoice.
Webhooks and SSE Streaming: Push agent events — assistant messages, tool results, approval requests, sub-agent spawns, compaction, timeouts — into your own apps in real time.
Memory Layers: Attach stored documents such as playbooks and policy sets to an agent so its guidance persists across objectives.
Outcome Feedback Scoring: Collect scored comments on each objective, attributed to the variation and model that produced it, to see which behaviors actually work.
Embeddable Widgets: Drop an agent experience into any frontend as a widget rather than building the conversational surface yourself.

Operational Exception Handling: Run an agent that detects stalled shipments or orders and reroutes them through your dispatch API within policy.
Safe Model Migration: Evaluate a new frontier model as a canary variation against live objectives before switching the default.
Wrapping Existing APIs: Turn internal OpenAPI endpoints into agent-callable tools without rewriting the services behind them.
Embedding Agent Chat in a Product: Ship a conversational agent surface into an existing frontend using widgets instead of building it in-house.
Cost Control at Scale: Use progressive discovery and live metering to keep context size and per-loop cost down as agent traffic grows.
Agent Quality Review: Compare scored feedback across variations to understand which prompt or model changes improved real outcomes.

Olostep Technologies

Freemium

A single web data API for AI agents that scrapes, crawls, maps, searches, answers, and monitors sites, returning clean Markdown, HTML, or JSON.

Unified Web Data API: Seven endpoints — scrapes, crawls, maps, batches, searches, answers, and monitors — behind one object-oriented client instead of separate services.
Clean Format Output: Returns any URL as Markdown, HTML, screenshots, or structured JSON so content is immediately usable as LLM context.
Site Crawling with URL Globs: Retrieve every page on a site with max-page limits and include/exclude glob patterns, then iterate pages and fetch content per page.
Batch Processing: Process up to 100,000 URLs in roughly five to seven minutes for large enrichment and indexing jobs.
Natural-Language Search and Answers: Query the web in plain language for ranked links, or use the answers endpoint to get an AI-composed response with sources.
Web Monitors: Set up monitors that fire when something changes across the web, such as a company publishing a new blog post.
JS Rendering with Residential IPs: All requests, including those on the free trial, are JavaScript-rendered and routed through residential IP addresses.
Agent-Native Access: Native Python and Node.js SDKs plus an MCP server and CLI so coding agents and AI tools can call Olostep directly.

RAG Pipeline Ingestion: Crawl documentation sites and convert every page to clean Markdown for embedding into a retrieval index.
Agent Web Browsing: Give an autonomous agent reliable read access to any URL through an MCP server rather than a brittle custom scraper.
Lead and Company Enrichment: Batch-process tens of thousands of company URLs to extract structured firmographic data.
Competitive Monitoring: Watch competitor blogs, changelogs, and pricing pages and get notified when they change.
Real-Time Research: Run natural-language searches and pull AI-generated answers with source links inside an application.
Price and Catalog Tracking: Scrape ecommerce listings on a schedule to keep an internal pricing dataset current.