Our Story - The Colony

Why we're doing this

AI adoption is often blocked by the same issues: sensitive data exposure, opaque behavior, vendor lock-in, and unpredictable usage costs. MOAA was created to unify cognitive reasoning, analytical execution, and governance inside a single modular framework-so teams can move faster without losing control.

How it began (and how the team formed)

MOAA began as independent research and engineering led by Pedro Rossa, focused on designing and building the orchestration architecture and deployments. As the system evolved, it became clear that enterprise-grade AI needs more than generative output-it needs a deterministic analytical core that produces explainable, auditable artifacts.

That's where Susana Almeida joined the work-initially through KML co-design, plus integration testing and validation of results, strengthening MOAA's analytical rigor and interpretability.

The idea behind "The Colony"

We took inspiration from biological colonies: specialized roles coordinated under one orchestration layer. In MOAA, ingestion and OCR behave like "scouts," execution units operate as "workers," vector indexes act as "pheromone memory," and governance policies enforce order and accountability.

What MOAA is

MOAA is built as a modular system with four foundational layers:

Cognitive Core (Main Model): contextual reasoning and orchestration across specialists
Execution Layer: structured routing across open-source specialist models, KML, and tools/APIs-with reliability controls (rate limits, retries, sandboxing) and observability
Local Knowledge Layer (Multimodal RAG): secure retrieval across documents, code, spreadsheets, OCR, and conversational memory, using vector indexes
Governance Layer: policy enforcement, traceability, and controls aligned with EU requirements

This combination enables a hybrid environment where reasoning, execution, and compliance are designed to work together.

Open-source models, predictable costs

A central design choice is avoiding dependency on per-token licensing. MOAA is designed around open-weight models and self-hosted inference, so cost becomes primarily infrastructure + operations-not usage surprises. We also emphasize version pinning and license metadata to keep deployments reproducible and auditable.

Security and local deployment by design

MOAA is designed for fully on-prem deployment (or controlled environments) to support data sovereignty, auditability, and regulatory alignment (GDPR / EU AI Act). The threat model includes risks like data exfiltration and prompt injection, with controls such as sandboxing, egress allow-lists, PII redaction, and signed artifacts/provenance.

KML: deterministic analytics inside the system

KML is MOAA's deterministic analytical engine, designed to produce explainable outputs-rules, metrics, and artifacts that support decisions and governance. It complements model-based reasoning with structured analytics to strengthen trust and accountability.

More than a platform: consulting and enablement

While MOAA is in development, The Colony already helps organizations adopt AI responsibly through:

Consulting & tailored solutions (with or without embedded AI)
AI Literacy & Productivity training to build awareness, safe usage habits, and scalable operating practices
Architecture & governance readiness so AI initiatives can move from pilots to production with confidence

We build with AI - every day

We don't just teach AI adoption - we live it. AI is deeply embedded in how we work and how we build MOAA.

We use AI continuously across our workflow to:

accelerate research and exploration of architectural options
draft and iterate technical documentation and specifications
generate and refine training content, playbooks, and templates
test messaging, structure stakeholder-ready narratives, and improve clarity
support rapid prototyping cycles and solution design

AI is part of our operating rhythm - not as a replacement for expertise, but as a force-multiplier for execution speed and iteration quality.

Where we're going

MOAA is still in active development, and we're onboarding a limited number of early partners to validate real use cases and shape the roadmap. If you want early access and direct input into what we build next:

Building sovereign, modular AI - without the per-token trap