Desktop App · macOS & Windows

Your entire fleet.
One command away.

Execute remote commands, stream scripts, orchestrate distributed compute, and run LLM inference across your Tailscale-connected machine fleet — all from a single desktop app.

scaleserve — remote runner
50+
Tailscale peers
supported per fleet
20
Parallel compute nodes
per distributed job
3
LLM inference modes:
Batch · Consensus · Ensemble
0ms
Extra infra required —
runs on your existing fleet
Capabilities

Everything your fleet needs,
in one sidebar

No more context-switching between SSH terminals, monitoring dashboards, and access panels. ScaleServe consolidates every fleet operation into a single interface.

⚡
Remote Command Execution
Execute any shell command on any Tailscale peer. stdout and stderr stream live into the UI as the process runs — no waiting for completion. Includes built-in presets for GPU inventory, Ollama health checks, PyTorch CUDA verification, and vLLM status. Auto-detects SSH users across common Linux distros and AWS/OCI instances.
ssh subprocesslive stdoutabortpresetsuser autodetect
📡
Script Broadcast
Stream any local script into a remote machine's stdin over SSH. No file upload, zero disk footprint. Supports Python, Bash, Node.js, PowerShell, Ruby, and Perl. Interactive Python mode lets you send runtime input after the script starts running.
stdin pipepython3 -interactive
🔀
Parallel Multi-Device Runner
Run scripts across N machines simultaneously. Per-device output panels update live. Stop any individual job or kill all with one button. Mix different scripts for different machines in the same batch run.
Future.waitper-job stopN×M parallel
🗂️
Distributed Compute Engine
Split an input file across N nodes proportionally by RAM + GPU capacity using a weighted scoring algorithm. Each node processes its chunk in parallel. Merge outputs with concat or a custom bash command. Supports CSV, JSONL, binary, and any file format.
weighted splitSCP chunksmerge
🧠
Distributed LLM Inference
Distribute prompt batches across GPU nodes running Ollama. Three modes: Batch splits prompts proportionally by GPU throughput. Consensus sends all prompts to every node for multi-perspective answers. Ensemble round-robins for load balancing. Results stream in real time with per-node prompts/sec metrics and ETA. Automatically checks VRAM capacity before assigning work and unloads the model after the job to free GPU memory.
Ollama APIbatch · consensus · ensembleVRAM checkreal-time PPSJSONL export
📊
Fleet Resource Monitoring
Poll CPU, RAM, and GPU metrics from fleet machines every 5 seconds via SSH. Platform-aware: uses nvidia-smi, rocm-smi, or Apple Silicon APIs.
5s pollGPU detectNVIDIA/AMD/M-series
🔑
SSH Key Management
Generate RSA keypairs, auto-install public keys on remote machines via a one-time bootstrap key, and sync the team keypair through the backend. SSH Doctor runs diagnostics on any node to identify and explain connectivity issues.
RSA keygenteam syncSSH Doctor
👥
Team Access Control
Workspace-scoped membership with owner, admin, and member roles. Granular permission flags control exactly what each member can do. New members join via OTP invite — no shared credentials ever. Full audit trail of every remote execution.
OTP invitepermission flagsaudit logs
🖥️
Device Fleet Browser
Searchable, real-time inventory of all Tailscale-connected peers. Filter by name, IP, OS, or online status. Devices with SSH profiles link directly into Remote Runner with the machine pre-selected.
tailscale statussearch & filterOS icons
How it works

One SSH subprocess. Infinite reach.

Every feature — from a single command to a 500-prompt LLM batch — reduces to the same primitive: an SSH connection routed through Tailscale's encrypted WireGuard overlay.

01 — DISCOVER
Tailscale peer list
ScaleServe calls tailscale status --json to discover every peer — DNS names, IPs, OS, and online status — with zero extra configuration.
02 — AUTHENTICATE
RSA key-based SSH
All fleet traffic uses RSA key auth over WireGuard. BatchMode=yes and ConnectTimeout=8 ensure no interactive hangs on unreachable nodes.
03 — EXECUTE
Streaming subprocess
Process.start() streams stdout and stderr line-by-line into the UI. Files stream through stdin — nothing written to remote disk unless you explicitly ask.
04 — PERSIST
Backend + local cache
Every run is logged to a local JSON cache and synced to FastAPI + PostgreSQL. The app works fully offline — backend sync is best-effort, never blocking.
ScaleServe Desktop
Overview — fleet metrics
Remote Runner — SSH exec
Distributed Compute
LLM Inference Engine
SSH Key Management
Members & Audit Logs
→
Tailscale Fleet (WireGuard)
gpu-node-1.tailnet
gpu-node-2.tailnet
gpu-node-3.tailnet
edge-machine.tailnet
on-prem-server.tailnet
... up to 50 peers
+
FastAPI Backend
/auth — JWT + OTP + MFA
/workspace — members + perms
/sync — machine snapshots
/sync — execution logs
/sync — SSH keypairs
PostgreSQL 16
Who it's for

Built for teams running
GPU and compute fleets

ScaleServe is for small, technical teams who already use Tailscale and want to stop fighting their infrastructure.

Fleet Owner
MLOps Lead · Infra Engineer
  • Bootstrap workspace and onboard GPU nodes
  • Set granular per-member permission flags
  • Review full remote execution audit trail
  • Manage team SSH keys centrally
AI Researcher
ML Researcher · Data Scientist
  • Batch LLM inference across GPU cluster
  • Stream training scripts to GPU nodes
  • Monitor per-node VRAM usage and ETA
  • Export JSONL results from inference runs
DevOps / SRE
DevOps Engineer · SRE
  • Run health checks across 10+ machines at once
  • Deploy monitoring agents in parallel
  • Use preset commands for GPU and Ollama checks
  • Diagnose SSH issues with SSH Doctor
New Team Member
Onboardee · Any role
  • Join network via OTP — no shared credentials
  • Pull team SSH keys automatically from backend
  • Run only what your permission flags allow
  • Get fleet access in minutes, not days
Built with
Flutter (macOS · Windows) FastAPI + Python 3.11 PostgreSQL 16 Tailscale / WireGuard Ollama / vLLM SSH subprocess layer JWT + bcrypt + OTP