Stop Designing Databases.
Describe Your World.
Metroknome is a cloud-native platform that deploys into your own AWS environment. You describe the objects and relationships that matter to your business. The platform handles how that data is stored, versioned, and accessed — across whatever industry you operate in.
A Different Starting Point
The conventional approach
- → Hire database architects to design schemas
- → Choose and configure individual database products
- → Create complex schema to force fit information
- → Lose context and traceability at every boundary
- → Repeat for every new domain, system, or vendor
The Metroknome approach
- → Deploy the platform into your AWS environment
- → Describe the objects relevant to your business
- → Describe the relationships between those objects
- → Describe the operations performed on those objects
- → Build applications, agents, and analytics on top
The underlying storage — across graph, relational, NoSQL, time-series, and object stores — is handled by the platform's FPOS architecture. Your team never chooses a database, designs a schema, or writes a data replication pipe. They describe their domain and get to work.
What You Do. What the Platform Does.
Deploy the Metroknome Platform
Deploy into your own AWS environment via infrastructure-as-code. The full persistence layer, security model, and administration interfaces are running in your account — with no ongoing vendor dependency.
Describe your business and provide access
Use the administration interface to define the things and activities that matter to your organization, how they relate to each other, and grant your users the appropriate level of access.
Build or buy applications on the platform
Developers and partners build workflow-focused applications on top of Metroknome's APIs. Applications are concerned with user experience and process — not with where or how data is stored.
Analyse your data freely and without manipulation
Data scientists and AI agents access data that is already fully discoverable and contextualized within your business environment. No ETL, no normalization, no ransformation required before analysis can begin.
The Same Platform. Any Domain.
Legacy data siloes without ontologies are preventing technology — including AI — from solving broad societal problems. The examples below show how the same Metroknome platform would be configured for four distinct industries. The objects and relationships change. The platform does not.
Medicine & Biopharma
The cost of researching and developing medicines is negatively impacted by poor knowledge management. Data about compounds, experiments, samples, and results lives in disconnected systems that cannot reason across each other.
Objects Defined in Ontology
Key Relationships Captured
- ⬡ Batch derived from Synthesis
- ⬡ Small Molecule made for Protein Target
- ⬡ Experiment follows Assay Protocol testing Small Molecule Batch
- ⬡ Synthesis QC performed on Instrument to verify Small Molecule Batch purity
- ⬡ Sample Prep performed on Small Molecule Batch priot to Experiment
Environmental Monitoring
Earth's ecosystem complexity cannot be represented with the digital precision needed to make sustainable decisions. Monitoring data is siloed by geography, agency, and instrument — with no unified model of how it connects.
Objects Defined in Ontology
Key Relationships Captured
- ⬡ Station monitors Habitat Zone over time
- ⬡ Sample collected from Water Body at GPS coordinates
- ⬡ Contaminant detected in Sample at measured concentration
- ⬡ Species observed in Habitat during Survey Event
- ⬡ Trend derived across Station readings over configurable time window
Energy Grid Management
Energy grids are antiquated and unadaptable to modern mixed-source generation. Without a model that captures every node, flow, and event with relationships intact, prediction and efficiency optimisation remain impossible.
Objects Defined in Ontology
Key Relationships Captured
- ⬡ Node connected to Transmission Segment with capacity attributes
- ⬡ Generation Asset feeds one or more Nodes
- ⬡ Sensor monitors Node and emits time-stamped Load Readings
- ⬡ Outage Event affects Demand Zone with duration and cause
- ⬡ Maintenance Work Order executed against Asset with crew and parts
Construction & Infrastructure
The cost of building infrastructure is negatively impacted by the lack of software capable of coordinating supply chains, trades, regulations, and physical progress in a single coherent model.
Objects Defined in Ontology
Key Relationships Captured
- ⬡ Work Order assigned to Trade Contractor on Site
- ⬡ Material consumed by Work Order with quantity and lot
- ⬡ Inspection validates Work Order against Regulation
- ⬡ Delivery links Material to Site with chain of custody
- ⬡ Project progress derived from Work Order completion states
What Comes With the Platform
Metroknome ships with everything needed to configure, operate, build upon, and analyse your business data — without requiring specialist infrastructure knowledge from your team.
Administration Interfaces
For operators & platform owners
Browser-based administration interfaces ship with the platform and require no custom development. Platform owners use these to manage the full lifecycle of their Metroknome environment.
User and Access Management
Create and manage users, roles, and team structures. Define who can view, create, or modify each object type.
Version Manegement
Check and PULL version updates on your schedule without vendor dependency.
Object Configuration
Define and evolve your ontology — the things and activities that matter to your business.
APIs for Builders
For developers & partners
Self-documenting APIs — contextualized within your ontology — are the surface through which applications interact with the platform. Builders focus entirely on workflow and user experience. The question of where and how data is stored never enters the conversation.
Workflow-Focused Applications
Applications make work better and faster using real things and activities — the platform handles the data.
Versioned & Discoverable
Every endpoint is documented, versioned, and reflects the client's own object definitions through a consistent framework.
Partner Ecosystem
Third-party developers and system integrators can build on the same surface as first-party apps
Data & AI Access
For analysts, scientists & agents
Because data is captured with full context — ontology, relationships, provenance, and timestamps — it is immediately consumable. There is no preparation step before analysis can begin. Data scientists and AI agents work directly with data that already reflects the meaning your organisation assigned to it.
Curate on Capture
Data are captured directly into the defined ontology — raw, derived, or interpreted.
Fully Contextualized
Every data item carries its ontological context — what it is, where it came from, and what it relates to
AI-Ready
Vectorized data endpoints are generated in near-real-time from existing definitions for use agerntic or ML workflows
Development Status
The platform is in pre-alpha. Each layer is production-grade before the next begins.
- Client Infrastructure Stack (IaC)
- Platform Admin Service & Interface
- Authentication & Authorization
- System Ontology Management Service
- Self-Service Version Updates
- Analytics Data Ensemble
The FPOS Architecture
Understand how data is actually fragmented and stored across the database ensemble.
Metroknome Labs
The first domain application built on this platform — purpose-built for biopharma R&D.
Get Involved
Investor, partner, or early adopter — reach out and start a conversation.