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

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

Olostep

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.

Freemium

A router for voice AI that benchmarks 56 speech and language models language by language, then routes each session to the one that wins.

Language-by-Language Benchmarks: 56 speech and language models measured across ten languages, exposing that a model topping the English table may have no published rank anywhere else.
Cost-Versus-Accuracy Charts: Word error rate plotted against dollars per minute for each pipeline stage — STT, LLM, TTS and speech-to-speech — so a model choice is a priced trade-off, not a guess.
Managed Router: A hosted, provider-neutral data plane at router.speko.dev that selects the winning model per session using the measurements and fails over before a response is returned.
Typed Contracts: Public OpenAPI and AsyncAPI specifications for the Router, so integrations are generated rather than hand-rolled against an undocumented endpoint.
Open Gateway Runtime: A customer-side runtime with native LiveKit and Pipecat services offering provider-direct streaming and local BYOK credentials, keeping your vendor relationships intact.
Drop-In Framework Integration: Swap STT, LLM and TTS in a LiveKit AgentSession for Speko equivalents with credential_source="auto" and model="auto" and get routing without restructuring the agent.
MCP Server: Point Claude Code or Cursor at mcp.speko.ai to query models, voices and benchmark data from inside a coding agent.
Two Pricing Paths: Either add 5% on top of a provider's published rate while routing your own spend, or take the bundled Speko infrastructure rate of $0.09 per minute across all three legs.

Multilingual Voice Products: Ship a voice agent to non-English markets and route each language to the model that actually performs best there.
Vendor Selection Research: Use the published benchmarks to decide which STT or TTS provider to sign with before committing to a contract.
Voice Cost Optimization: Trade a small accuracy delta for a large cost reduction by picking a model at the right point on the WER-versus-price curve.
Failover and Reliability: Keep voice sessions alive through a provider outage with pre-response failover across the routed model pool.
LiveKit or Pipecat Migration: Add measured routing to an existing agent stack by swapping in Gateway services rather than rewriting the pipeline.
Agent-Assisted Model Research: Query the benchmark data from Claude or Cursor over MCP while writing the voice integration.