Sandboxed.Sh vs Voyage AI

Side-by-side comparison of features, pricing, and ratings

Analysis generated Live tool data as of 2026-10-30
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Sandboxed.Sh or Voyage AI: which should you choose?

DimensionSandboxed.ShVoyage AI
Core FunctionOrchestrator for AI coding agentsEmbedding & reranking models for RAG
Data ControlSelf-hosted, data stays on your serverAPI-based, cloud hosted with SOC 2/HIPAA
Primary UsersDevelopers running long coding tasksEnterprise RAG teams, legal/finance
IntegrationsClaude Code, OpenCode, Codex, Gemini, GrokAny vector DB or LLM (no built-in list)
Best ForUnattended, long-duration agent runsHigh-accuracy retrieval on domain-specific docs

Choose Voyage AI if your priority is accuracy and low-cost vector storage for enterprise RAG on finance, legal, or code. Choose Sandboxed.Sh if you need a self-hosted orchestrator to run AI coding agents for hours without session limits, keeping sensitive code on-premises.

Sandboxed.Sh
Sandboxed.Sh

Orchestrate Claude Code, Codex, Antigravity, OpenCode and Grok from one self-hosted control plane for AI coding agents.

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Voyage AI
Voyage AI

Voyage AI embedding models and rerankers for high-precision RAG retrieval, now part of MongoDB

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Pricing
Paid
Paid
Plans
Hobby$19/mo
Pay-as-you-goUsage-based
Custom / On-premiseContact sales
Popularity
7 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
WebMobileDesktopAPI
WebAPI
Categories
🛠️ Autonomous Coding Agents⚙️ Developer Infrastructure
🗄️ Vector Databases & Retrieval
FeaturesSandboxed.ShVoyage AI
One composer for Claude Code, Codex, Antigravity, OpenCode, Grok and cloud adapters
Three execution modes: local Mac via Tauri runner, private Linux nodes, cloud coordinators
Self-hosted Core backend on Linux or via Docker install
Isolated systemd-nspawn containers with cgroup resource caps on your own servers
Host-directory workspaces for agents that need files in place
Subscription sign-in for Anthropic, OpenAI, xAI, Kimi and Google Antigravity in Providers
CLIProxyAPI Plus OAuth ownership via SANDBOXED_OAUTH_OWNER=cli-proxy to avoid refresh-token races
Live provider plan and quota status inspection with model routing
/plan mode with native question and approval cards
/goal mode for autonomous multi-turn execution
Durable follow-up queue that sends on turn completion or immediately
schedule_wakeup durable mission wake-ups and automatic interrupted-run recovery
Cross-machine mission transfer with SHA-256 verified file manifests and Git bundles
Docked /btw side-agent panel for side questions with shared workspace context
REST API, SSE event stream and unified sandboxed-mcp server for automation
General-purpose embedding models for search and RAG
Domain-specific embedders tuned for finance, legal, and code
Company-specific embedding models fine-tuned on proprietary data
voyage-multimodal-3.5 embeds images and text in one retrieval pipeline
voyage-context-3 pairs chunk-level detail with global document context
rerank-2.5 rerankers with instruction following to steer ranking
rerank-2.5-lite for a lower-cost price-performance point
3x-8x shorter vectors to cut vector search and storage costs
4x smaller model with faster inference
2x cheaper inference with superior accuracy
32K-token long-context support for embedding long documents
Batch API for large-scale embedding workloads
Plug-and-play with any vectorDB and any LLM
SaaS and in-VPC customer tenant deployment
SOC 2 and HIPAA compliance
IntegrationsSandboxed.ShVoyage AI
GitHub
Claude Code
Codex
Antigravity
OpenCode
Grok
ChatGPT
Hermes
Cursor Cloud
Grok Bot
CLIProxyAPI Plus
Docker

Who should pick Sandboxed.Sh, and who should pick Voyage AI?

  • Enterprise RAG architect in finance
    Pick: Voyage AI

    Voyage AI's domain-specific finance model and 32K context ensure high accuracy on financial documents, with low-dimensional embeddings reducing vector DB costs.

  • DevOps engineer running multi-hour code refactors
    Pick: Sandboxed.Sh

    Sandboxed.Sh's Docker isolation and long agent runs (up to 10 hours) are ideal for unattended, sensitive code tasks with full data control.

  • Solo developer building a RAG app on legal docs
    Pick: Voyage AI

    Voyage AI's legal-specific model and low-dimensional embeddings improve retrieval without huge infrastructure costs, though pricing requires sales contact.

  • Startup needing transparent, low-cost agent orchestration
    Pick: Sandboxed.Sh

    Freemium pricing and self-hosted option ($30/mo server) give predictable costs and control, with free tier for experimentation.

Frequently Asked Questions

Sandboxed.Sh vs Voyage AI: which should you choose?

Choose Voyage AI if your priority is accuracy and low-cost vector storage for enterprise RAG on finance, legal, or code. Choose Sandboxed.Sh if you need a self-hosted orchestrator to run AI coding agents for hours without session limits, keeping sensitive code on-premises.

Can I use Voyage AI for free?

No, Voyage AI requires contacting sales for pricing; no free tier is mentioned.

Does Sandboxed.Sh run AI models itself?

No, it orchestrates agents like Claude Code, OpenCode, etc.—you bring your own AI.

Which tool is better for data privacy?

Sandboxed.Sh, since it's self-hosted and data never leaves your server.

Does Voyage AI support multimodal?

Yes, voyage-multimodal-3.5 has been announced, extending to multimodal retrieval.

Can Sandboxed.Sh integrate with GitHub issues?

Yes, agents can read and resolve GitHub issues; skills are stored in a git repo.

Is Voyage AI's pricing enterprise-only?

Pricing is custom and contact-based, typically for enterprise customers.

How long can agents run on Sandboxed.Sh?

From 10 minutes up to 10 hours, depending on configuration.

What integrations does Voyage AI support?

It works with any vector database or LLM via API; no pre-built integration list is provided.

What else are Sandboxed.Sh and Voyage AI compared with?

Where can you read more about Sandboxed.Sh and Voyage AI?

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Analysis generated by our model pipeline from live data: