Enterprise Solutions
From one working pilot to a company that runs on it.
The hard part was never the first system. It is the platform, the governance, the funding model and the people work that let forty more follow without forty more integrations and forty more arguments.
- Workflows on shared platform
- 40+Workflows on shared platform
- Lower cost per new use case
- 62%Lower cost per new use case
- From idea to production, steady state
- 9 weeksFrom idea to production, steady state
- Faster internal approval cycles
- 3xFaster internal approval cycles
Portfolio view
LiveWorkflows running on one shared platform
23
Systems registered
47%
Run cost reduced
14
Countries live
Every AI system in the organisation has a named owner, a data classification and a verified benefit.
The problem
Eleven pilots. Two in production. Nobody can explain why.
Each team solved its own integration, chose its own model, wrote its own prompt library and negotiated its own security review. The work was duplicated, the risk was inconsistent, and the second use case cost as much as the first. That is not an AI problem. It is an operating-model problem.
What it costs you
- Every team rebuilding the same integrations and evaluation tooling
- Security review as a queue that takes eleven weeks per project
- No shared view of what AI is running, where, or at what cost
- Model and vendor sprawl with no consistent data handling
- Business cases written in isolation and never verified after launch
What we build
The parts that make it survive production.
Every engagement includes all of this. None of it is an upgrade tier.
AI platform foundation
Shared gateway, model routing, secret management, evaluation tooling and observability — so the tenth use case costs a fraction of the first.
Governance that ships
A risk framework with tiers, pre-approved patterns and a fast lane for low-risk work. Designed to accelerate delivery, not to create a committee.
Integration fabric
One well-tested set of connectors to your core systems, versioned and owned centrally, instead of nine teams writing nine ERP clients.
Portfolio management
A single register of every AI system in the organisation: owner, purpose, data classification, cost and measured benefit.
Cost governance
Per-team budgets, chargeback, model routing policies and anomaly alerts. Finance gets a forecast rather than a surprise.
Change and adoption
Role redesign, training and communications built into delivery — because the systems that fail are rarely the ones that failed technically.
Legacy modernisation
Strangler-pattern migration off systems that cannot participate, sequenced so nothing depends on a big-bang cutover.
Vendor strategy
Honest build-versus-buy analysis, contract review and exit planning, including where a platform product beats anything custom.
Where it pays
Real workloads. Real numbers.
Results are drawn from production engagements and measured against a pre-engagement baseline.
Shared services transformation
Finance, HR and IT service operations consolidated onto one automation platform with a common exception model.
$4.1M annual run-rate saving
AI centre of excellence
Standards, reusable components, an internal enablement programme and a review process that clears low-risk work in days.
Time to production down from 7 months to 9 weeks
Regulated AI rollout
Model risk documentation, bias testing and explainability evidence produced as part of delivery rather than retro-fitted for the regulator.
First-pass regulatory approval on 6 of 6 systems
Merger integration
Two operating models reconciled through an automation layer while the underlying system consolidation ran on its own timeline.
Day-one operational continuity, zero manual bridges
Global rollout
One platform, region-specific data residency, local language handling and country-level policy variation.
14 countries live in 11 months
Cost recovery programme
Model routing, caching and workload placement reviewed across the portfolio against measured quality thresholds.
AI run-cost reduced 47% with no quality loss
How it runs
From first conversation to running system.
- 01Stage 1
Portfolio and readiness
What is running, what it costs, what it returns, and where the organisation genuinely is on data, skills and governance.
3–4 weeks
- 02Stage 2
Platform and guardrails
Shared foundation and a risk framework with a fast lane, proven by putting two real use cases through it.
8–12 weeks
- 03Stage 3
Scale the pipeline
A steady cadence of use cases delivered on shared components, with your teams progressively taking the build work.
Quarterly
- 04Stage 4
Hand over the keys
Your platform team runs it. We move to advisory, and the engagement gets smaller on purpose.
Month 9+
Technology
Chosen by evaluation, not by preference.
We build on what fits your constraints and what your team can maintain. Nothing here locks you in.
- Your repositories, your cloud account, your licence
- No proprietary runtime you have to keep paying for
- Documentation written for the engineer who inherits it
Platform
- Kubernetes
- Terraform
- AWS Bedrock
- Azure AI Foundry
- Vertex AI
- LiteLLM gateway
Governance
- NIST AI RMF
- ISO 42001
- EU AI Act readiness
- Model cards
- Evaluation registries
Core systems
- SAP
- Oracle
- Workday
- Salesforce
- ServiceNow
- Dynamics 365
Data
- Snowflake
- Databricks
- BigQuery
- dbt
- Kafka
- Unity Catalog
How we price it
Three ways in. A stop point at each one.
Enterprise programmes are scoped in stages with a decision point at each boundary. You are never asked to fund a multi-year transformation on the strength of a slide.
Readiness review
Fixed price · 4 weeks
An honest assessment of your AI portfolio, platform maturity and governance, with a costed roadmap and a sequencing recommendation.
- Portfolio audit and cost analysis
- Platform and data readiness assessment
- Governance gap review
- Costed 12-month roadmap
Platform programme
Staged · 6–12 months
Shared platform, governance framework and the first wave of use cases, delivered alongside your teams rather than around them.
- Shared AI platform build
- Risk framework with fast-lane approvals
- Reusable integration fabric
- First 3–5 production use cases
- Enablement and capability transfer
Embedded partnership
Annual · retained
A standing senior team inside your organisation, accountable to your delivery targets and reviewed against them quarterly.
- Dedicated multi-disciplinary pod
- Architecture and governance authority
- Continuous delivery pipeline
- Executive and board reporting
- Priority incident support
Questions
What buyers ask about enterprise solutions
Direct answers, including the ones that are inconvenient for us.
Still deciding?
Send the question to a senior engineer instead of a form. You will get a straight answer, and a no if that is the honest one.
In our experience it is rarely the technology. It is that nobody owned the operating change, the security review had no fast lane, and the business case was never re-tested after launch. We address those three specifically: a named business owner per use case, a risk framework with pre-approved patterns for low-risk work, and mandatory benefit verification 90 days post-launch.
No, and building one first is a common expensive mistake. Ship one or two real use cases, notice what they had in common, and extract the platform from that. We usually start the platform work in parallel with the second use case, not before the first.
We classify each use case against the risk tiers, and for anything above minimal risk we produce the technical documentation, data governance records, human-oversight design and post-market monitoring plan as delivery artefacts. Producing that evidence during the build costs a fraction of reconstructing it afterwards.
Yes. We are usually the AI and automation specialists inside a wider programme. We are explicit about the boundary and we do not compete for scope mid-flight — that arrangement is agreed in writing at the start.
Typically 500 employees and up, or smaller organisations with unusually complex regulatory or operational demands. Below that, a single well-built system usually beats a platform, and we will say so.
Three numbers, agreed before we start: cost per new use case, time from approved idea to production, and verified benefit realised against business case. All three are reported quarterly, including when they are moving in the wrong direction.
Start the conversation
Bring us the enterprise solutions problem you have already tried to solve.
Ninety minutes with our engineers. You leave with a systems map, a shortlist and an honest read on whether this is worth doing at all.
What to expect
- No pitch deck, no obligation
- Senior engineers in the room
- A written plan within five days
Prefer email?
support@cyberxsolutions.us