jurniti vs Vurge: Features, Pricing & Which Is Better (2026)

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

jurniti

Paid

Managed 24/7 hosting for coding agents, each running in its own Firecracker microVM with your own model keys and no token markup.

Firecracker microVM Isolation: Every agent runs in its own KVM-backed virtual machine with hardware-enforced tenant isolation instead of a shared-kernel container.
Bring Your Own Key: OpenRouter, OpenAI or Anthropic keys live only inside the customer's VM — jurniti never sees them, never proxies calls and never marks up model spend.
Multi-Harness Support: Runs Claude Code, Codex CLI, OpenClaw, Hermes, OpenCode, Devin CLI, Mastra and Pi, each in its own dedicated microVM.
Fleet CLI: A jurniti command-line tool to boot agents, list fleet status, dispatch work and copy results back, so the whole fleet is managed from a terminal.
Swarm Runtime: Boots dozens of isolated microVM workers at once and dispatches the same brief to every worker, with results collected in a single command.
Flat Per-VM or Hourly Billing: A flat monthly or annual price per agent VM, or per-second metered On-Demand and Spot pricing for bursty workloads, with prepaid credits.
Automated Provisioning: Payment triggers a magic-link sign-in and an auto-provisioner that has a live microVM running in about three minutes with no human in the loop.
Custom Subdomain and Sidecars: Pro tiers add a custom subdomain, alongside separate microVM services for multi-agent communication and long-term agent memory.

Always-On Coding Agents: Keeping a Claude Code or Codex agent working on a backlog overnight without leaving a laptop running.
Secure Key Handling: Running agents for a team that cannot let model API keys leave its own infrastructure boundary.
Parallel Agent Fleets: Dispatching one brief to fifty isolated workers to compare approaches or parallelize a large refactor.
Bursty Batch Work: Using per-second Spot or On-Demand VMs for agents that only run a few hours a day, paying only for active runtime.
Self-Hosting Alternative: Replacing hand-rolled VPS setups for open-source agent harnesses like Hermes, OpenClaw or OpenCode.
Long-Running Agent Memory: Pairing an agent VM with a dedicated memory microVM so knowledge persists between sessions.

Freemium

AI-powered web data extraction that integrates with Google Sheets to simplify and automate web research.

Google Sheets Integration: Operates inside Google Sheets (as an add-on or functions) to populate cells and ranges directly from web sources without leaving the spreadsheet environment.
Structured Extraction: Identifies and converts semi-structured web content (tables, lists, product details) into normalized rows and columns suitable for analysis.
URL-to-Table Parsing: Accepts URLs or page inputs and extracts tabular and key-value information automatically, reducing manual copy-paste and reformatting.
Data Cleaning and Normalization: Applies basic normalization and formatting (dates, numbers, trimming) so imported data is ready for filtering, sorting, and pivoting.
Bulk Processing & Pagination Handling: Processes multiple URLs or paginated content in batch to gather multi-page results into single spreadsheet views.
Workflow Automation: Enables repetitive research tasks to be run programmatically from the sheet (e.g., refresh, scheduled pulls) so data stays up-to-date.
AI-powered extraction of web data into Google Sheets
Direct integration with Google Sheets (marketed as a research buddy in Sheets)
Automates web-research and data-population workflows for spreadsheets
Designed for non-technical users to collect and organize web data inside Sheets

Market Research: Collect product attributes, prices, and availability from multiple e-commerce pages into a single sheet for competitive analysis.
Lead Enrichment: Extract contact details and company metadata from directory listings and import them into CRM-prep spreadsheets.
Content Research & Curation: Pull headlines, summaries, and author info from articles across sites to assemble editorial research lists.
Price Monitoring: Periodically extract pricing and stock data from supplier pages to track changes over time in a sheet.
Data Aggregation for Reports: Combine tabular data from varied web sources into consolidated sheets for visualization and reporting.
Academic or Competitive Intelligence: Gather structured facts and references from public web pages to support research and citations.
Market research and competitor data collection into spreadsheets
Lead generation and contact/public data aggregation
Content research and citations collection for reports
Automating recurring web-data collection tasks into Google Sheets