How we structure every engagement
Before work begins, we establish a precise scope — what will be delivered, on what timeline, and how success is defined. During work, we maintain regular contact and surface issues early. At the end, your team has documented, operable systems and the knowledge to manage them.
This is not novel. It is simply disciplined. We apply the same structure across all three services because we believe it produces better outcomes than informal working relationships.
Discovery
Understand your environment, constraints, and what good looks like
Scope Agreement
Document deliverables, timeline, and evaluation criteria
Delivery with Review Points
Work in iterations with regular check-ins and early issue flagging
Handover & Knowledge Transfer
Documentation, training sessions, and capability transfer to your team
AI Observability &
Monitoring Setup
Most AI systems in production operate without adequate visibility. Teams find out something has gone wrong through downstream failures — not through direct observation. This service implements the instrumentation and tooling that gives your team a clear window into how your models are performing day to day.
The engagement covers the full monitoring layer: metric definition, dashboard creation, data drift detection, prediction confidence tracking, system health alerting, and integration with your existing operations toolchain. It closes with a monitoring playbook and runbook for common scenarios.
What you will have after this engagement
- Configured dashboards your team can read and act on
- Alert logic tied to meaningful thresholds, not defaults
- A written playbook for how to respond to common model issues
- Team capability to maintain and extend the system
Well-suited use cases
- Fraud detection where transaction networks matter
- Supply chain risk modelling with multi-tier relationships
- Knowledge graph completion and entity resolution
- Recommendation systems over user behaviour graphs
Graph Neural Network
Solutions
For problems where the relationships between entities carry as much signal as the entities themselves, standard tabular or sequential models consistently underperform. Graph neural networks address this — but only if the data is structured appropriately and the architecture is chosen for the specific problem.
This engagement begins with a structured assessment of whether a graph-based approach is actually warranted. If it is, we proceed through graph data modelling, network architecture selection, training pipeline design, and integration with your data infrastructure. The iterative evaluation model means you see working outputs before the engagement closes.
Enterprise AI Platform
Selection & Setup
AI/ML platform choices are consequential and not easily reversed. The wrong selection can constrain your team for years — through poor fit with existing infrastructure, skills gaps, or misaligned cost structures. This engagement is designed to help your organisation make this decision once, carefully, and build on a solid foundation.
We begin with a thorough requirements analysis — covering team skills, existing infrastructure, budget parameters, and strategic goals. We then conduct a structured vendor evaluation, run a proof-of-concept phase with shortlisted options, and assist with full deployment. If you are migrating from an existing platform, migration planning is included.
For organisations that want to
- Build a durable AI infrastructure that scales with the organisation
- Move off an existing platform that no longer fits their needs
- Make a platform decision with a clear rationale, not a vendor pitch
Choosing the right solution
If you are unsure which service fits your situation, this matrix may help. You can also contact us to discuss.
| Your situation | Observability | GNN | Platform |
|---|---|---|---|
| Models in production with limited visibility | |||
| Relational data where graph structure is critical | |||
| Need to select or migrate AI/ML infrastructure | |||
| Building a complete AI capability from a new platform | |||
| Fraud or network analysis problems |
Discuss your situation
with the Neuralith team
Tell us what you are working on. We will respond within one business day with a frank assessment of whether we can help.
Contact Neuralith