Enterprise AI Architecture
We design the shared architecture and platform that lets AI scale across the organisation.
Enterprise AI Solutions
Enterprise AI Solutions
Trusted across 20+ countries by Fortune 500 companies and growth-stage brands
We help large organisations deploy AI at scale, across departments, systems and geographies, with the architecture, governance and MLOps to run it reliably. Move beyond isolated pilots to AI that delivers enterprise-wide impact. Over a decade of experience, 250+ digital solutions delivered.
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What are enterprise AI solutions?
Enterprise AI solutions are AI systems built to operate at organisational scale, integrated across multiple departments, data sources and applications, and governed to meet security and compliance requirements. Unlike a single use case build, enterprise AI needs shared architecture, MLOps, governance and change management so it can scale reliably. Noseberry designs and delivers enterprise AI that connects to your existing estate and grows across the business.
Key takeaways
- Enterprise AI operates at scale, across departments, systems and regions.
- It needs shared architecture, MLOps and governance, not just individual models.
- The common failure is staying stuck in pilots, so we engineer for production and scale.
- Security, compliance and change management are core, not optional.
2M+Lives touched
15+Fortune 500 clients
20+Countries served
250+Digital solutions delivered
What we build
Our enterprise AI solutions
MLOps and Model Operations
We build the pipelines, deployment and monitoring that keep many models running reliably.
Cross-System Integration
We connect AI across your ERP, CRM, data platforms and applications enterprise-wide.
Data Foundations for AI
We help unify and prepare enterprise data so AI has a reliable, governed source of truth.
Enterprise Governance and Security
We embed responsible AI, access controls, audit trails and compliance across every deployment.
Change Management and Adoption
We plan the rollout, training and operating changes that make enterprise AI stick.
Scaling and Optimisation
We scale successful use cases across teams and geographies while managing cost and performance.
Where it delivers value
Where enterprise AI delivers value
Standardising AI delivery across business units
Automating high-volume processes across departments
A shared platform so teams build faster and safer
Consistent governance and security across all AI
Cost efficiency through shared infrastructure and reuse
How we work
Our five-phase process
For enterprise programmes we prove value on a priority use case first, then scale on shared foundations, so you avoid a risky big-bang rollout.
1
Discovery and Audit
We map your estate, data and priorities across the organisation.
2
Strategy and Roadmap
We sequence quick wins and platform investments into a phased plan.
3
Rapid Proof of Concept
We prove value on a priority use case first.
4
Build and Integrate
We build shared foundations and integrate enterprise-wide.
5
Deploy and Optimize
We scale across teams and regions, managing cost and performance.
Timeline
How long does enterprise AI take?
A first priority use case can reach production in a few months, while a full enterprise platform and rollout is a phased programme, often 12 to 20 weeks per major phase. We sequence quick wins first so value funds the next stage.
Technology we use
Models & LLMs
- OpenAI GPT
- Anthropic Claude
- Llama
- Mistral
- Gemini
Data platforms
- Snowflake
- Databricks
- Kafka
- Spark
Cloud & MLOps
- AWS
- Azure
- Google Cloud
- MLflow
- Kubeflow
- Docker
- Kubernetes
Enterprise systems
- Salesforce
- HubSpot
- Zoho
- Okta
- Your ERP
Security and compliance
Security and governance at the core
Enterprise AI is built with security and governance at the core, including private hosting, encrypted pipelines, role-based access, audit trails and responsible AI controls. We align to GDPR, HIPAA and SOC 2, deployed on AWS, Google Cloud and Azure.
GDPRHIPAASOC 2
Real success storiesFinTech · Enterprise programme PropTech · Multi-market rollout E-Commerce · Group-wide
Outcomes we have driven
Challenge
AI scoring worked in a pilot but couldn't scale across the business.
Solution
A shared MLOps platform and governance layer to run many models reliably.
Impact
93% of fraud caught pre-payout, an estimated $4.2M saved annually.
Challenge
Valuation AI was siloed to one market with no path to scale.
Solution
Shared foundations to roll the solution out across three markets.
Impact
40% faster property valuations with higher consistency.
Challenge
Personalization was inconsistent across brands and regions.
Solution
A shared recommendation platform standardised across business units.
Impact
+28% lift in conversion rate.
Sector-anonymised outcomes shown until named clients are approved.
Why Noseberry
Why choose Noseberry for enterprise AI
Specialist
AI, Cloud and Data is our core, no generalist dilution.
Production-first
We take AI beyond pilots to enterprise-wide production.
Governed by design
Security, compliance and oversight built into the platform.
Proven at scale
15+ Fortune 500 clients, 250+ solutions across 20+ countries.
Enterprise AI, answered.
Shared architecture, MLOps, governance, security and the ability to scale reliably across departments and regions, not just a single working model.
Most stall in pilots because they lack shared foundations, governance and a scaling plan. We engineer for production and scale from the start.
Yes. We integrate AI across your ERP, CRM, data platforms and applications rather than replacing them.
Through private hosting, encryption, access controls, audit trails and responsible AI, aligned to standards like GDPR, HIPAA and SOC 2.
We prove a priority use case first, then scale on shared foundations with change management and training, avoiding a risky big bang.
Ready to scale AI across your organisation?
Book your free 30-minute AI strategy session and we will map an enterprise AI roadmap.
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