Enterprise AI Development Company

Focused AI applications with clean data typically deploy in 12–16 weeks. Enterprise platforms with multiple integrations and compliance requirements range from 20–36 weeks.

Engagements range from $180,000 for focused applications to $2M+ for enterprise platforms with multiple model systems and integrations. We provide ROI projections before contracts are signed.

Yes. We have delivered AI systems in healthcare and financial services environments subject to HIPAA, GDPR, SOC 2, and MiFID II. Compliance controls are designed in from the architecture phase.

We prefer to work with existing infrastructure. Full rebuilds are rarely required — targeted data remediation on priority datasets is typically sufficient.

Every system includes monitoring for accuracy, data drift, latency, and availability. We provide monthly performance reports and manage retraining cycles.

Yes. We have delivered integrations with SAP S/4HANA, Salesforce, Oracle ERP, Epic, Workday, and ServiceNow.

Yes. For organisations with data residency or air-gapped environment requirements, we deploy using containerised on-premise infrastructure.

Poor data quality is common. Our discovery includes a data quality assessment and remediation roadmap. A perfect data estate is not a prerequisite.

Both. For data privacy or high-volume inference, we fine-tune open-source models. Where appropriate, we leverage OpenAI, Anthropic, and AWS Bedrock.

We are a solutions-led engineering organisation, not staff augmentation or an API wrapper shop. We architect and build AI systems end-to-end with a consistent production deployment track record.

If you already know which system you need built, we can scope and start development directly. If you're still evaluating where AI creates the most value, our AI Consulting engagement is the faster, lower-risk starting point — it feeds directly into this build track without re-scoping.

Yes. Engagement structure differs — startups typically start with a focused MVP-scoped build, while enterprise engagements involve more upfront architecture and compliance review — but the same senior engineering team and production standards apply to both.

Every engagement starts under mutual NDA before any data or requirements are shared. Discovery itself is a structured, time-boxed assessment — not an open-ended sales process — and produces a scoped proposal, not just a conversation.