AI that understands your environment - not just your prompts.

Stellr builds the infrastructure and products for agentic systems that carry context forward: compress repetitive signal, retain intent across sessions, and turn environmental cues into precise action - without forcing users to re-explain themselves every time.

What we do View products
01

Less prompting

Shrink the manual context users must ship into every request. Context should arrive structured, not typed from scratch.

02

Inherent context

Specs, sessions, and memory give models dense environmental state so inference spends budget on reasoning - not reconstruction.

03

Shared substrate

One stack under Orrin, Yabble, NextUp, and developer tooling - products compose instead of reinventing context plumbing.

01 // What we do

We make context the command surface.

Traditional AI waits on explicit prompts and forgets everything between sessions. We engineer the opposite: environment-aware systems that already know enough to act.

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The friction we remove

Inefficient interactions

Most AI still depends on hand-authored prompts, brittle scrapes, and repeated API round-trips. Users spend the majority of interaction time reconstructing context the system should already hold - workflow state, prior intent, tool outcomes, and environmental cues.

Continuity breaks across sessions. Integration into real hardware and daily tools is shallow. The model is powerful; the context path is not.

  • - Prompt crafting dominates time that should go to outcomes
  • - Session amnesia forces users to re-teach the same facts
  • - REST loops hide mid-flight tool status and agent coordination

What Stellr builds instead

We flip the default: structure the environment so context is inherent. Endpoints declare meaning. Sessions stream state. Memory retains intent over time. Products and developer tools plug into the same substrate rather than inventing private context formats.

The result is agentic software that can move from observation → compression → action with far less explicit instruction - and with shared contracts across the stack.

  • + Standardize - unified protocols so context works across apps and agents
  • + Measure - capture behavioral nuance and intent, not just raw events
  • + Trade - exchange structured insight between systems and users in real time
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Core loop // Actions ↔ Data
Compress

Actions into data

SaaS surfaces produce limited, repetitive actions. True awareness is not hoarding every token of dense history - it is recognizing repetition and compressing it into durable, reusable signal. We turn streams of behavior into structured context models that agents can reason over without replaying the entire past.

Drive

Data into actions

Inversely, compressed contextual state can autonomously drive the next move. By linking subtle environmental cues to the exact action required, models stop waiting for perfect prompts and start participating in the workflow - scheduling, drafting, navigating, coordinating tools - when the situation already contains the answer.

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Shared infrastructure // Exegesis Explore Exegesis

One substrate under every Stellr product

Exegesis is not a consumer surface - it is the protocols, specs, realtime paths, and memory layers every Stellr system plugs into. Its job is narrow and deliberate: reduce how much explicit context users must feed a model, and increase how much context the model already holds.

A

Web Specifications

Machine-readable endpoint semantics (.espec) so models understand surfaces without heavy scraping or oversized prompts.

B

Realtime transport

WebSocket-first execution for bidirectional streams, Terminal Sessions, handlers, senders, and low-latency structured payloads between agents and tools.

C

Contextual memory

Episodic / vector state so intent and history persist across sessions instead of resetting every call - the foundation for long-horizon autonomy.

D

Interactivity specs

Declarations that let pages and tools react to user behavior in real time, feeding agents live situational context as work unfolds.

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Cost

Fewer tokens, fewer loops

Dense specs and session state replace multi-hop REST scraping and oversized system prompts. Inference spends budget on reasoning, not reconstruction.

Consistency

One context model

Products and SDK agents share the same notions of session, payload shape, and memory - so the ecosystem composes instead of fragmenting.

Velocity

Build product, not transport

Handlers, senders, and specs sit on a packaged connection layer. Teams ship domain behavior rather than websocket auth, framing, and session bookkeeping.

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For developers

Centralized execution & OrrinSDK

Bind tools, open Terminal Session handlers, and let Exegesis own auth, framing, and lifecycle. Autonomous workflows emerge from structured context - not from stitching another prompt chain.

CE Docs OrrinSDK
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02 // Products

Tools that sit on the same context stack.

Each product is a different surface - mobile, desktop, workflow, infrastructure - wired into Exegesis so memory, sessions, and specs stay consistent.

Orrin
Flagship · iOS

Orrin

Spatial, agentic workspace for advanced notes (OrrinInfinity), planning, and running AI tools and agents without constant prompting. Orrin adapts to how you work - carrying project-scale context through Exegesis sessions and memory so the board, agents, and tools share one coherent state.

  • › Infinite canvas for notes, agents, and structured work
  • › Agentic tasks grounded in live session context
  • › Extensible via OrrinSDK for custom tools & agents
Explore Orrin Install on iOS
Yabble
Beta · Desktop

Yabble

Desktop intelligence that works from what is already on your machine and screen. Yabble runs agentic tasks via Terminal Sessions, browses with Exegesis Specifications for minimal token use, and acts on your behalf - without turning every step into a chat transcript.

  • › Host-machine tasks through Terminal Session handlers
  • › Spec-backed web understanding (less scrape, more structure)
  • › Multi-step loops kept coherent by shared memory
Explore Yabble
NextUp
Pre-release

Pragmos

Plan, schedule, journal, and navigate your workflow in one place. Pragmos is built so planning artifacts are not dead documents - they become contextual fuel for agents and the rest of the Stellr stack, closing the gap between intention and execution.

  • › Unified surface for plans, schedules, and journals
  • › Workflow state designed to feed agentic systems
  • › Continuity with Orrin and Exegesis memory paths
Explore Pragmos
NextUp
Infrastructure

Exegesis

The shared infrastructure under every Stellr product: web specifications, realtime WebSocket execution, episodic memory, and interactivity contracts. Exegesis is how we make context awareness infrastructure - not a feature bolted onto each app independently.

  • › .espec & ESPECI for structured web & UI contracts
  • › Terminal Sessions, handlers, and sender protocols
  • › Central MCP-style core for unified memory across apps
Explore Exegesis espec
Ecosystem

Surfaces across mobile, desktop, protocol, and developer tooling - one context model.

Orrin Yabble NextUp Konekt
03 // FAQ

Clarifications

Short answers to how we think about context, products, and the stack.

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What exactly is context awareness?
Context awareness is an AI system’s ability to understand and adapt to a user’s circumstances, needs, and intent in real time. Instead of relying only on manual, explicit prompts, it uses environmental cues, structured specs, session state, and behavioral signal - so responses and actions fit the situation without re-explaining the world on every turn.
How does “promptless” AI function?
Promptless does not mean silent magic with no controls. It means the system is not blocked waiting for a perfectly written instruction. With permissioned access to structured context - screen/workflow state, specs, memory, and live sessions - agents can suggest or execute the next action from what is already true in the environment, while users still steer outcomes.
What is Exegesis relative to Orrin or Yabble?
Orrin, Yabble, and NextUp are product surfaces. Exegesis is the shared infrastructure beneath them: specifications, realtime Terminal Sessions, handlers/senders, memory, and interactivity contracts. Products differ in UX and platform; they share the same context model so agents and tools compose instead of each inventing private plumbing.
How do developers build on Stellr?
Through OrrinSDK, Terminal Session handlers, Centralized Execution, and Exegesis specifications. You bind tools and implement handler logic; Exegesis owns connection lifecycle, auth handshakes, and structured streaming. That lets custom apps, agents, and tools ride the same realtime paths as first-party products. Start at the OrrinSDK docs and CE documentation.
Is connectivity to external tools fully open?
Terminal Sessions and related surfaces are still early. External connectivity for tools, models, and agents is intentionally constrained while the architecture matures - to keep safety and reliability boundaries clear. All usage of Stellr infrastructure is subject to our Terms & Conditions and developer policies.
Where do I follow research and releases?
The Stellr newsletter carries research notes, product updates, and release dispatches. For hands-on surfaces, see product pages for Orrin, Yabble, NextUp, and Exegesis, plus API and SDK documentation linked in the footer.
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Context awareness is infrastructure, not a chat skin. That is the bet - and what every Stellr surface is built to prove.