Solutions

What we do

The team has delivered the components behind these solutions in enterprise and product environments. We scope the combination each client needs. When a solution joins several disciplines, the proposal states what we will assemble and who owns each part.

Digital systems and applications

Customer-facing software that is fast, easy to change and connected to the systems behind it.

We build public web interfaces, product front ends, internal operational screens and the backend services that support them. A scope may include technical search accessibility, Core Web Vitals, authentication, browser automation, payment or messaging connections, analytics and deployment.

Web applications and product interfaces using Next.js, React, Vue.js and TypeScript
Backend services, REST APIs, streaming events and background workers
Authentication, typed API contracts and generated clients
Technical SEO, crawl and indexation diagnostics, structured data and site performance
Browser automation, data ingestion and workflow interfaces
Prototyping, wireframing, minimum-version delivery and product iteration

Delivered

Von’s full-stack AI applications, Aaron’s production APIs and event-driven backends, Oceanic Atlas, and a completed technical web diagnostic covering a 54-URL crawl, field and laboratory performance checks, structured-data review and competitive benchmarking.

Boundary

Our delivered work supports interface, web application and backend delivery. We do not present a conventional e-commerce storefront or a general custom business application as prior delivery.

Data and decision platforms

One governed set of numbers, so two reports never disagree.

We turn operational data into a governed platform for reporting, analytics and downstream applications. Work can cover source assessment, ingestion, lakehouse or warehouse architecture, catalogue migration, dimensional modelling, business rules, data quality and Power BI or custom reporting layers.

Databricks, Delta Lake, Unity Catalog and medallion architecture
Data warehouse design, star schemas, conformed dimensions and fact modelling
ETL and ELT across enterprise databases, files, APIs and legacy sources
Data migration, schema discovery, type translation and validation
Governed catalogues, quality rules and curated analytical layers
Power BI and custom executive analytics
Tested metric and semantic layers

Delivered

A Databricks modernisation from Hive Metastore to Unity Catalog, medallion architecture, dimensional warehouse design, reusable NoSQL migration, AS400-connected data services and analytical layers consumed by Power BI. Oceanic Atlas turned an unmodelled fleet-operations source into a dimensional model and placed published metrics in a regression-tested semantic layer.

Enterprise integration and modernisation

Systems bought at different times talk through managed APIs, not manual transfers.

We connect systems that were bought or built at different times. An engagement may replace point-to-point transfers with managed APIs and pipelines, modernise a legacy backend, migrate data into a governed store or place a stable service layer in front of an older system.

API gateway architecture, OAuth2, rate limiting and routing policy
Payment, messaging and contact-centre integration
CRM, ERP, mainframe and document-system integration
Event-driven services using queues, streams and real-time messaging
Backend modernisation across PostgreSQL, MongoDB and managed cloud databases
Webhooks, idempotent processing and recovery for stale or failed jobs

Delivered

Ownership of an Apigee gateway layer across a payment provider, SMS provider and contact-centre webhooks; Zoho CRM and dual-ERP integration across Syspro and NetSuite; production services and a claims system connected to AS400; a document migration above 100,000 records; and an image-generation backend rebuilt as an event-driven system.

AI-enabled knowledge and operations

AI with a defined job, grounded sources, access boundaries and evaluation.

We build AI applications around a defined job and controlled information boundary. Suitable work includes assistants grounded in company documents, separate knowledge scopes for different users, scored intake and lead workflows, document review, multi-agent processes and AI features inside a larger application.

Multi-agent system design and orchestration
Retrieval over private documents and operational data
Knowledge isolation, vector stores, document chunking and similarity search
Prompt design, hallucination reduction and grounded responses
Evaluation harnesses and feedback loops
Multi-model routing and AI cost control
Make.com, Zapier, n8n and GoHighLevel automation
AI-assisted intake, scoring, notification and reporting

Delivered

A seven-agent production workflow with isolated knowledge stores for two business partners, a Make.com lead-scoring pipeline for an operating business, and applications for job matching, prompt engineering and medical study. Those applications cover browser ingestion, document retrieval, vector search, model routing, evaluation and full-stack product interfaces.

Cloud platforms and delivery systems

An environment your team releases into through automation, not manual infrastructure work.

We build the environment software teams release into. Work can include Azure architecture, private Kubernetes, Terraform, containerisation, CI/CD, reusable deployment templates, developer self-service, observability and promotion across development, UAT and production.

Azure Kubernetes Service, Helm and private-cluster architecture
Terraform and reproducible infrastructure
GitHub Actions, Azure DevOps and Jenkins pipelines
Container build, scan and deployment workflows
Developer self-service and reusable platform templates
Prometheus, Grafana and Azure Application Insights observability
Databricks release automation
Cloud resource sizing, scheduling and FinOps review

Delivered

A private Azure Kubernetes Service platform provisioned through Terraform, standardised Helm deployments across microservices, self-service release operations, automated Databricks promotion from development through production, non-production cluster scheduling, resource right-sizing and a zero-downtime PostgreSQL migration.

Reliability, security and managed operations

A production estate that is monitored, patched and remediated under change control.

We assess and operate defined production estates across Azure and AWS. Coverage can include monitoring, incident response, identity and access, certificates, patching, backup, disaster recovery, networking, firewalls, vulnerability remediation and formal change control.

Azure and AWS compute, storage, networking and managed services
Monitoring, daily health checks and priority incident response
Identity, role-based access and certificate lifecycle management
Linux and Windows administration and patching
Palo Alto firewalls, F5 load balancers and hybrid network monitoring
Backup, restore validation and disaster-recovery exercises
Qualys and Microsoft Defender vulnerability remediation
Static, dependency, dynamic, container and secret scanning
ITIL, ServiceNow, change boards and regulated operating controls

Delivered

Enterprise cloud operations across aviation, healthcare and medical devices, entertainment, automotive and financial services. Ron has handled critical incidents to service levels, cloud and network operations, annual SAP disaster-recovery drills and vulnerability remediation under formal change. Ralph has embedded security scanning into release pipelines, blocked releases on critical findings and evidenced control coverage to security and audit teams.

Boundary

Managed operations use a defined service boundary and response model. Ownership, capacity and service levels are confirmed before they appear in a proposal.

How the capabilities combine

A client rarely needs the whole catalogue. One team can join the required parts without losing accountability between them.

A reporting programme might begin with source assessment, continue through ingestion and dimensional modelling, then add a Power BI layer and automated deployment.
A customer portal may need a web interface, an API gateway, CRM and payment connections, cloud infrastructure and production monitoring.
An internal AI assistant may need document ingestion, access-separated retrieval, an application interface, evaluation, deployment and operating controls.

Each is treated as one engagement with one owner, one sequence and explicit boundaries. Specialists enter where the scope needs them. We do not place every member on every account or imply that every discipline is available on demand.

Sectors the team has delivered in

Insurance
Consumer finance
Construction
Global consulting
Early-stage technology
Aviation
Healthcare and medical devices
Entertainment
Automotive
Financial services

Not sure which of these you need? That is what the diagnostic is for.

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