Plug in a fully contextualized AI chief of staff.
Starling runs on your organization’s sovereign intelligence, so it reasons from your business instead of generic patterns.
Your memory, and everything it becomes.
1. Your Sovereign Repository.
Starling starts by provisioning a Notion workspace, where it writes your Constitutional Memories — the fifteen fundamentals every business needs to codify. Cancel and the repository remains yours. The First Fifteen give any advanced AI model the ability to extrapolate additional memory, so you stay because Starling works better for your team, not lock-in.
2. Starling at Smart OS.
After establishing your Constitutional Memory, Smart OS activates and Starling becomes a model-agnostic AI chief of staff. It assembles context for session-based AI, helping you draft, decide, and plan with governed memory. Ask it anything about your business, and it keeps that context current as the work moves.
3. Starling with Smart Office.
With your foundation in place, Starling builds out your extended canon and architects your active work, so every project and campaign inherits the latest context. As work completes, Starling extracts the patterns, and your repository becomes a compounding asset.
Where your token usage actually goes.
Translating between lossless memory and lossy documents.
Your Org Library is your memory repository — where all work originates. It stores lossless Markdown artifacts that minimize token usage. This means everyday strategic queries are covered by your seat cost under normal use.
Two Workspace operations convert your memory from/to the lossy documents that drive heavy token usage: Excavation parses uploaded context, and Delivery turns out the finished documents that leave the building.
Both live in a separate repository, Resources — uploads coming in, work going out. You spend on translation between lossless memory and lossy documents. Your memory stays light and governed.
How model selection works
Starling works with the best of every model: Claude for work, GPT for voice, and Gemini for deep analysis.
They draw from the same pool, each on its own meter. Costs are transparent in your settings.
Claude Work
Build canon, convert documents, run strategy and queries.
Meters by tokens.
GPT Voice
Talk to your brain, hands-free, for quick answers.
Meters by the minute.
Gemini Analysis
A second-model pass when you want one.
Meters per run.
Start with Seat 1. Grow by certification.
Starling starts with a single seat — the System Librarian who builds your Constitutional Memory. Once you define your canon, you can invite your team, up to five seats. Beyond five, we open seats through certification. Here’s why:
Every business needs a dataset for AI and somebody to administer it. We provide those standards, across four types of memory: System, Persistent, Active, and Learned.
System memories are what every organization runs on, persistent memories are what rarely change, active memories are our daily work, and learned memories are institutional wisdom. Make them machine-executable and own your intelligence.
Platform dependency is a single point of failure.
Your prompts, memory, and workflows live inside a platform you don’t control. One policy change, one outage, one acquisition — and the knowledge you built vanishes. Starling eliminates that dependency entirely.
Declare your data independence.
Start Starling by Wednesday, July 22 (midnight EDT) and become a founding member. You’ll get 25% off usage for 60 days.
Once you complete Onboarding, you’ll have the opportunity to create a per-seat subscription. We limit this to 5 initially, so your designated administrator learns natural language classification. More seats are available as you scale.
What you need to know
What exactly is Starling?
What does the $99/mo seat include?
What is Constitutional Memory?
How are excavation and delivery billed?
Why only five seats at first?
Do I keep it if I cancel?
Will my data be used to train a model?
Put your intelligence
to work.
Founder’s offer good until midnight Eastern time on July 22, 2026.