ENTERPRISE KNOWLEDGE GRAPH

Unlock Organisational Intelligence

Where Structure Meets Story.

Gigno™ is an Enterprise Knowledge Graph that unifies your company’s explicit operational structures and its tacit problem-solving contextual history to improve organizational effectiveness, decision-making, and business continuity.

THE ARCHITECTURE

Complex Logic. Effortless Adoption.

01 / STRUCTURE
02 / NARRATIVE
03 / MEMORY

Institutional Structure

Operational Narrative

Institutional Memory

Map your foundational framework.

Connect your operational structure and governance entities.

Track your contextual history.

Monitor operational issues, remediation paths and real-world outcomes.

Embed learning into your workflow.

Anchor operational takeaways so future teams build on past experience.

Gigno™ handles the complex relational math of an Enterprise Knowledge Graph behind the scenes so your teams don't have to.

We replace rigid database queries and messy documentation frameworks with a clean, intuitive workspace.

Users effortlessly log operational realities, while our backend context engine automatically maps the permanent, invisible intelligence of your enterprise.

INDUSTRIES WE SERVE

Built for Knowledge-Intensive Organizations

Government Healthcare Financial Services Oil & Gas Technology Professional Services Manufacturing Telecommunications

Wherever operational knowledge is created, Gigno transforms it into a connected organizational asset.

Gigno™ is designed for organizations where operational knowledge, institutional memory, and contextual decision-making are critical to long-term performance.

Strategic Value. Engineered for Context.

For Enterprise Leadership & Teams
For Strategic Partners

Competitive Moat: Rooted in deep, proprietary graph architecture that cannot easily be replicated.

Compounding Enterprise Value: Every contribution increases the long-term value created by the platform.

Predictable Enterprise Retention: Secures long-term institutional value driven by deep operational habits and structural necessity.

Zero-Friction Interfaces: Built intentionally for rapid, effortless everyday adoption across departments.

Native Contextual Alignment: Mapped instantly at point of entry, providing real-time relationships across input, viewing, and retrieval.

Institutional Resilience: Safeguards critical organizational knowledge through turnover, restructuring, and succession.

CATEGORY COMPARISON

LEGACY EKG PLATFORMS

Operating Model: Heavy, complex data-engineered enterprise fabrics.

Ease of Use: Opaque systems requiring specialized software developers and technical training.

Implementation Timeline: Months of intense IT consulting, custom integrations, and custom engineering.

Infrastructure Location: Massive, custom-built private cloud networks.

Pricing Model: Enterprise licensing with complex procurement and long-term commercial negotiations.

DRIVES / WIKIS

Operating Model: Folder trees of static, disconnected files.

Ease of Use: High manual upkeep, open-ended blank pages, and intense cognitive fatigue.

Implementation Timeline: Zero setup but becomes chaotic and disorganized instantly.

Infrastructure Location: Shared, multi-tenant cloud storage.

Pricing Model: Linear per-user SaaS licenses.

GIGNO™

Operating Model: A living operational ecosystem linking organizational structure to decision intelligence.

Ease of Use: Intuitively designed to reduce administrative burden while guiding contextual capture.

Implementation Timeline: Rapid deployment with a fully operational, structured workspace within days.

Infrastructure Location: A dedicated, isolated workspace environment.

Pricing Model: Enterprise licensing designed to encourage organization-wide adoption, not individual seats.

The Next Generation of Organizational Intelligence

Designed to Reward Contribution

Most enterprise knowledge systems fail because capturing knowledge feels like extra work with little immediate reward.

Gigno™ replaces open-ended documentation with structured micro-inputs and contextual prompts presented at the point of work.

A Self-Reinforcing Knowledge System

Every contribution enriches the organization’s institutional memory, while every interaction returns relevant organizational context to the user, creating a continuous feedback loop of collective contribution and organizational value.

Why Now?

Organizations have never generated more operational knowledge.

Yet most of it remains fragmented across documents, conversations, disconnected systems, and institutional memory.

As enterprises increasingly adopt AI, its effectiveness becomes dependent on organizational context. This creates the need for a new foundational layer. One that captures, connects, and preserves contextual knowledge as a structured organizational asset.

Gigno was built to provide that layer.

FAQs

What is Gigno™?

Gigno™ is an Enterprise Knowledge Graph that unifies your company’s explicit operational structures and its tacit problem-solving contextual history to improve organizational effectiveness, decision-making, and business continuity. Gigno™ bridges the gap between operational structure and decision intelligence.

Who is Gigno designed for?
How is pricing structured?
What about security and privacy?
Can I upgrade later?

Pricing is structured in annual tiers based on your overall organizational footprint. This eliminates the fluctuating, unpredictable costs of traditional per-seat software licensing.

Yes. You can seamlessly transition to a higher workspace tier as your team scale and organizational footprint expand.

Gigno™ is engineered for scaling companies and enterprise teams looking to secure institutional memory, eliminate silos, and protect operational continuity.

Every deployment receives a dedicated, isolated workspace environment. Your organizational data remains strictly partitioned, private, and compliant with enterprise security standards.

Secure Your Organizational Context

Deploy a dedicated relational graph workspace in days. Protect critical organizational knowledge and prevent institutional memory loss across every function.