Year 0 · Investment
- Deploy investment capital
- Strengthen AI infrastructure
- Build technical capability
- Acquire structured domain intelligence
- Accelerate model engineering
- Develop specialised AI
- Commercialise products
RM20M is the current post-money valuation. The Year-5 outcomes below are scenario-based and depend on execution, recurring revenue, specialised IP, SME adoption, enterprise traction and regional scalability.
RM20M is the starting valuation. Enterprise value must be earned through product, IP and adoption milestones.
Valuation follows execution. Time alone does not create enterprise value.
Three scenarios, not a forecast.
Illustrative only. Future valuation is not guaranteed.
AINNA's valuation thesis is broader than revenue alone.
AINNA's objective is to convert domain knowledge into specialised intelligence and reusable IP.
A successful specialised model can serve many customers without equivalent linear growth in human resources. That scalability can contribute to enterprise value, but it does not guarantee a specific valuation.
AINNA's long-term objective is to demonstrate measurable economic impact across thousands of SMEs.
AINNA's technology may become strategically relevant to public-sector SME programmes, financial institutions, industry bodies and enterprise ecosystems if measurable productivity and economic impact can be demonstrated at scale.
More adoption creates more validation, better systems and stronger IP.
Domain validation and product feedback should come from approved and legally permissible data, not from any assumption that private customer data is automatically used to train AINNA models.
Valuation follows execution. These gates help show what has to be earned.
Illustrative only. Future valuation is not guaranteed and ownership can change with dilution or corporate actions.
| Company valuation | Undiluted 10% stake value |
|---|---|
| ~RM150M | ~RM15M |
| RM300M | RM30M |
| RM500M | RM50M |
| RM1B+ | RM100M+ |
Illustrative only. Future valuation is not guaranteed. Actual investor ownership and value may change due to future fundraising, dilution, share structure, company performance and other corporate actions.
This framework is meant to show how AINNA could move from a RM20M post-money company toward a much larger AI company through execution, IP creation, recurring revenue, specialised models, SME economic impact and scalable adoption.
The AINNA CLI runs entirely on your infrastructure with the models you configure. Choose Install for your platform, then use Quick Start to connect a provider and begin.
AINNA CLI runs on your infrastructure with the models you configure. It is built for controlled, private, operational use.
387 installs
Current release: 2.0.29 · 2026-10-17
curl -fsSL https://ainna.bond/ainna-agent/install | sh
curl -fsSL https://ainna.bond/ainna-agent/install | sh
iwr https://ainna.bond/ainna-agent/install.ps1 -useb | iex
pkg update && pkg install -y curl unzip
Linux · macOS · Windows · Android legacy package v1.18.33 · current release 2.0.29 · downloads from ainna.bond
AINNA CLI v2.0.29 does not currently include an Android or Termux build. The older ARM64 Debian package remains available as a legacy download.
The available Android ARM64 .deb is the previous v1.18.33 release; it is not a Termux installer.
Keep the main agent engine on Linux for easier background work, file access, service control, and deployment reliability.
Best model: Linux core + Android companion. Android can act as a thin controller, local client, or on-device runtime when needed.
There is no one-line installer for Android/Termux in v2.0.29. The previous ARM64 Debian package is available for compatible Debian-based environments.
Install AINNA, connect your own provider, select a model, and send your first request.
ainna. On first launch it opens the AINNA panel.ainna providers login --provider opencode. AINNA keeps your credential in your own isolated AINNA data directory; it does not use a shared account.ainna model use big-pickle, or list available models with ainna models.Linux-first core with Android companion is the best setup for the AINNA CLI.
You want mobile control, on-device testing, or a thin runtime wrapper for ARM64 Android environments.
You want the main agent engine, background services, file operations, and predictable deployment behavior.
Do not make Android the only base unless the product is specifically a mobile-first agent. For the core CLI, keep Linux as the source of truth.
Yes. The CLI is designed to run on your infrastructure with your chosen models and provider setup.
Yes. You can connect providers and switch models without rebuilding the whole setup.
Release notes are published in the changelog, and this block can link back to it anytime.
Linux is the recommended core for background work and deployment. macOS is supported for local development, Windows via PowerShell, and the previous Android ARM64 .deb remains available as a legacy package.