Aroora AI Labs
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Independent research lab · aroora.ai

Building the open agentic stack.

Aroora AI Labs ships open infrastructure for trustworthy agentic AI — a token-efficient format (ISON), property graphs for context (ISONGraph), a multi-agent protocol engine (MAPLE), deterministic context shaping (Contexel) and local multi-model inference (SnapLLM). Repository first, product second.

Explore ISON →
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“AI systems should be verifiable, not just impressive.”

The stack

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01 / Verifiable by design

Canonical serialization, byte-identical context shaping, replayable agent runs — every layer of the stack can be checked, diffed and reproduced.

02 / Token economics matter

Context windows are the scarce resource. ISON cuts payloads 30–70% versus JSON; ISONGraph fits 3× more graph into the same window.

03 / Open by default

MIT-licensed specs, reference implementations and reproducible benchmarks — private work becomes public the moment it is stable.

Flagship · v1.0.4 · PyPI npm crates.io

ISON

A minimal, token-efficient data format optimized for LLMs and agentic AI workflows.

Familiar tabular patterns models have seen billions of times. 30–70% fewer tokens than JSON, lossless round-trip, and byte-identical canonical output across all seven implementations.

Explore the repo →
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MIT licence7 implementations860+ tests
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87 tokens34 tokens · −61%
And the rest of the lab
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Repository index

Everything the lab maintains, across every organisation. Private repositories are marked and can be hidden — future repos slot into the same template.

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Repo template
A · editorial
B · docs shell
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private — opens when stable

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Playground

json → ison, right here in the page
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Demo

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Quickstart

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README

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Why

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Status

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Architecture

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Maintainer

MV
Mahesh Vaikri
AI Architect @ Dell Technologies · Founder, Aroora AI Labs · 11 publications

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Quickstart

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Architecture

architecture diagram

Maintainer

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Mahesh Vaikri
Founder, Aroora AI Labs · GitHub ↗

Lab notes

Releases, benchmark results and format decisions — written when something ships, not on a schedule.

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In the lab

What is being built next, published early so people can tell us we are wrong — or ask to help. Nothing here is a commitment.

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express interest →

Get in touch

Commercial licensing, research collaboration, sponsorship, or a question about a spec — pick the closest inbox.

Research & sponsorship
research@aroora.ai
MAPLE commercial licence
mahesh@mapleagent.org
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