jurniti vs Rep by Clarify: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of jurniti and Rep by Clarify — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
jurniti
jurniti
Managed 24/7 hosting for coding agents, each running in its own Firecracker microVM with your own model keys and no token markup.
Key features
- 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.
Best for
- 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.
Rep by Clarify
Clarify
AI-native CRM that automates updates, follow-ups, and pipeline hygiene for founder-led startups.
Key features
- Automated Updates: Uses AI to capture signals from sales interactions and automatically update contact and deal records to reduce manual data entry.
- Smart Follow-ups: Generates and schedules context-aware follow-up tasks or messages based on conversation content and deal status to increase engagement.
- Pipeline Hygiene: Detects stale or at-risk deals, surfaces required next actions, and recommends prioritization to keep the sales pipeline healthy.
- Founder-Focused Workflows: Lightweight UX and prioritized automation designed specifically for founder-led teams to minimize CRM setup and maintenance overhead.
- Deal Prioritization: Scores or surfaces high-impact opportunities so small teams can focus efforts on deals most likely to close.
- Activity Capture: Continuously records and consolidates sales activities (calls, meetings, notes) to maintain an accurate timeline for each opportunity.
- Automated activity updates (auto-capture and log activities)
- Automated follow-ups and reminders
- Pipeline hygiene and cleanup automation
- Cloud-hosted SaaS CRM
- Developer integrations via SDKs and connectors (Go, Python, Node-RED/TypeScript)
- Multiple plan tiers including a free plan and Enterprise offerings
Best for
- Reducing CRM Data Entry: Automatically updating contact and deal records from sales interactions so founders spend less time on manual logging.
- Automated Follow-Up Sequences: Drafting and scheduling context-aware follow-ups after meetings or emails to maintain momentum on deals.
- Pipeline Cleanup and Management: Identifying stale opportunities and recommending next steps to improve forecast accuracy and sales throughput.
- Founder-Led Sales Execution: Enabling small founding teams to maintain a disciplined sales process without dedicating resources to CRM upkeep.
- Prioritizing Sales Work: Surfacing high-impact opportunities and next actions for limited sales capacity to maximize closed revenue.
- Founder-led startups automating CRM maintenance to focus on sales
- Small sales teams using automated follow-ups to increase conversion
- Engineering teams integrating CRM data via SDKs (Go, Python) into internal tools or pipelines
- Companies that need cloud-hosted, low-maintenance CRM with developer-friendly APIs and SDKs