STAN. Your Platform Knows How to Talk.

Strongly Technical AI Navigator. An autonomous agent that builds workflows from conversation, writes and deploys code, manages infrastructure, and operates every surface of the platform. Not a chatbot. An operator.

100+ MCP Tools 255+ Workflow Nodes Persistent Memory
Scope the First Engagement Talk to an FDE
STAN AI Assistant Interface

Three Modes. Complete Platform Control.

STAN operates the platform through distinct modes, each purpose-built for how teams actually work

Platform Mode

Full Platform Operations

The default mode. STAN manages the entire platform surface through conversation - deploy apps, provision databases, configure AI models, manage users, check costs, enforce governance.

  • App deployment and management
  • Add-on provisioning (databases, caches)
  • AI model configuration and routing
  • Cost tracking and optimization
  • User and team management
Workflow Mode

Workflow Builder

Describe what you need in plain language. STAN builds the complete workflow - discovers your services, adds nodes, configures connections, maps data flows, and tests execution.

  • 255+ nodes across 11 categories
  • Auto service discovery
  • Conditional routing and looping
  • Built-in testing and debugging
  • Agent nodes with MCP tools
  • Streaming voice agent workflows
Develop Mode

Code Development

Write production code, build full-stack applications, and deploy to workspaces. STAN integrates with Claude Code for AI-assisted development directly inside the platform.

  • Full-stack application development
  • Claude Code integration
  • Isolated workspace environments
  • Deploy from conversation
  • Code generation and review

Not a Chatbot. An Intelligent Agent.

STAN learns, remembers, adapts, and acts autonomously across the platform

Persistent Memory

STAN remembers your preferences, facts, and instructions across conversations. It learns that you prefer React, knows your timezone, and recalls your deployment patterns. Memory decays intelligently - recent context weights higher.

Personality Options

Three personality modes adapt STAN to how you work. Professional for structured, precise responses. Friendly for conversational, approachable assistance. Concise for brief, direct answers. Switch anytime from your profile.

Knowledge Powered by RAG

Retrieval augmented generation gives STAN access to the full platform knowledge base. It finds the right doc, tutorial, or example based on what you are actually doing. Semantic search, not keyword matching.

Skills System

15+ system skills covering every platform domain - from workflow building to governance compliance. Create your own reusable skills from conversations. Skills are recalled automatically when STAN detects relevant context.

Scheduled Tasks

Schedule STAN to run recurring operations - cost reports every Monday, drift checks on models daily, workflow deployments at specific times. One-time or cron-based scheduling with full execution tracking.

Autonomous Monitoring

Heartbeat system runs every 5 minutes. Failed workflows, crashed apps, unhealthy add-ons, model drift - STAN catches it and notifies you before you notice. Zero LLM cost for health checks.

100+ Tools. One Conversation.

STAN connects to the platform through the Model Context Protocol. Every operation you can do in the UI, STAN can do through conversation - and often faster.

Intelligent tool selection classifies your message and loads only the relevant tools. No bloated context. No confusion. STAN picks the right tool for the job.

100+
MCP Tools
255+
Workflow Nodes
15+
Skill Domains
11
Node Categories
Apps Workflows AI Models Databases Data Sources Workspaces Projects Cost Ops Governance Marketplace User Management Notifications Search Execution Monitoring Node Catalog Service Discovery Memory Management Context Management
> STAN, create a workflow that takes customer emails, extracts intent with AI, and routes support tickets to the right team
list_user_models() → GPT-4o, Claude Sonnet 4
create_workflow() → wf_8x2k
add_node("email-trigger") → node_1
add_node("ai-gateway") → node_2
add_node("switch-case") → node_3
connect_nodes() → 3 connections
configure_node() → intent extraction prompt
auto_layout()
Done. Workflow "Customer Email Router" is ready. It triggers on incoming email, classifies intent using Claude Sonnet 4, and routes to billing, technical, or general support. Want me to add Slack notifications for each route?

Commands That Do Real Work

Slash commands give you direct control. Type the command, STAN executes.

/model

Select your AI model to power STAN's capabilities

/workflows

Enter workflow builder mode - create from natural language

/develop

Enter develop mode - write and deploy production code

/skills

View system and custom skills STAN can use

/remember

Save a memory for STAN to recall in future sessions

/memories

List all active memories with creation dates

/sessions

Browse and resume past conversations

/tasks

View and manage scheduled recurring tasks

/context

Check token usage and available context window

/compact

Compress conversation history to save tokens

/exit

Exit current mode back to general platform mode

/help

Display all commands and current mode information

What STAN Actually Does

Real tasks. Real outcomes. Not hypotheticals.

Build Workflows From Conversation

"STAN, create a workflow that processes invoices, extracts data with AI, and updates our PostgreSQL database."

Result: STAN discovers your services, builds the complete workflow with data mappings, error handling, and conditional routing - then tests it with sample data.

Deploy and Manage Applications

"STAN, deploy my API service, connect it to the MongoDB add-on, and set up environment variables."

Result: STAN provisions resources, configures connections, deploys the app, and confirms it is healthy - all in one conversation turn.

Cost Optimization

"STAN, analyze our AI model usage across all teams and recommend cost optimizations."

Result: STAN pulls real usage data, identifies underutilized models, suggests cheaper alternatives for low-complexity tasks, and provides actual dollar savings.

Autonomous Health Monitoring

"STAN, schedule a daily check on all workflows and alert me if anything fails."

Result: Heartbeat system runs every 5 minutes - no LLM cost. Failed executions, crashed apps, and model drift trigger instant notifications.

Build Streaming Voice Agents

"STAN, create a streaming workflow for an outbound voice agent that calls customers about overdue invoices, looks up their account, and offers payment plans."

Result: STAN builds the full streaming pipeline with telephony trigger, VAD, STT, conversation memory, LLM with tool calling, TTS, and telephony response. It configures the disposition schema to capture call outcomes and connects the tool executor to your billing API.

Cross-Platform Operations

"STAN, set up a new project with a PostgreSQL database, connect my S3 bucket, and create a data pipeline workflow."

Result: STAN orchestrates across projects, add-ons, data sources, and workflows in a single conversation - operations that would take dozens of UI clicks.

Governance and Compliance

"STAN, show me which models are processing PII data and check their compliance attestation status."

Result: STAN audits model configurations, checks attestation records, identifies gaps in compliance policies, and generates a summary with recommended actions.

Context That Persists. Sessions That Resume.

STAN maintains conversation history, manages token budgets automatically, and lets you resume past sessions exactly where you left off.

  • Smart Context Management: Token budgeting with automatic compaction at 80% usage. Long conversations never break.
  • Session Persistence: Browse and resume past conversations. Pick up complex multi-step tasks days later.
  • Memory Across Sessions: Preferences, facts, and instructions carry forward. STAN remembers what worked last time.
  • Multi-Model Support: Choose from GPT-5 family, Claude Opus, Claude Sonnet, and more. Switch models mid-conversation.
  • Intelligent Tool Selection: STAN classifies your message and selects only the relevant tools from 100+. No wasted context.
> /sessions
Your recent conversations:
1. "Invoice Pipeline Setup" - Workflow Mode - 3 days ago
2. "API Service Deployment" - Platform Mode - 1 week ago
3. "Cost Analysis Q1" - Platform Mode - 2 weeks ago
> Resume 1
Loading session context...
Restoring workflow mode...
Resumed. You were building the invoice pipeline with 8 nodes. The AI extraction node still needs the output mapping configured. Want me to finish that?
> /remember I always use Claude Sonnet for classification tasks and GPT-4o for generation
Saved. I'll use Claude Sonnet for classification and GPT-4o for generation in future workflow configurations.

Measurable Impact. Real Numbers.

STAN reduces onboarding time, deflects support tickets, and drives feature adoption

75% Faster Onboarding

Hours, not days. Interactive guidance and contextual support get new users productive before the first standup.

80% Fewer Support Tickets

STAN handles the common questions. Your team focuses on strategic work. Support tickets drop. Everyone wins.

Full Platform Utilization

STAN surfaces capabilities teams did not know existed. Your investment delivers full value, not 30% of it.

Your Platform Has an Operator. Meet STAN.

100+ tools. Persistent memory. Three operating modes. See STAN build a workflow from conversation in the first engagement.

Scope the First Engagement Talk to an FDE