Generative AI Development Services

We implement grounding architectures including RAG, output validation layers, confidence scoring, factual consistency checks, and human review workflows for high-stakes content.

Yes. We deploy open-source foundation models on your own cloud infrastructure or on-premise environment using vLLM or Ollama — ensuring no client data leaves your security perimeter.

RAG grounds model responses in current, queryable knowledge bases — best for knowledge retrieval. Fine-tuning adapts model behaviour, tone, and format — best for style and terminology. Most enterprise deployments benefit from both.

Focused RAG applications with existing knowledge bases deploy in 8–12 weeks. Custom fine-tuned model applications with complex integrations require 14–20 weeks.

All fine-tuned models, prompt libraries, custom code, and AI-generated content are fully client-owned upon final payment.

Consistent output requires systematic prompt architecture, version-controlled templates, automated regression testing, and output format enforcement. We build these as standard components of every deployment.

Yes. We integrate with SharePoint, Confluence, Notion, S3, Google Drive, and custom document systems — building indexing pipelines, permission-aware retrieval, and synchronisation workflows.

Current frontier models support strong multilingual performance. For specialised domains or languages, we evaluate model performance against your accuracy requirements and implement language-specific validation.

Depending on your industry and geography: EU AI Act, NIST AI RMF, HIPAA for healthcare, GDPR for EU data subjects, and SOC 2 for enterprise SaaS. We design compliance controls into every deployment.

Yes. We conduct structured assessments identifying root causes — typically prompt architecture, retrieval quality, model selection, or missing validation layers — and deliver improvements with documented performance benchmarks.

Focused generative AI applications typically range $40,000–$150,000; enterprise systems with multiple integrations and validation layers range higher. We scope exact costs after a discovery call, not from a generic price list.

If the use case is already validated, we start building. If you're choosing between several possible generative AI applications, a short AI Consulting engagement scopes the highest-ROI option first — cheaper than discovering the wrong one mid-build.

Production generative AI systems need monitoring for output quality drift, cost-per-request, and model-provider changes. We offer post-launch monitoring and optimisation retainers scoped to your system's actual usage volume.

Yes — startup engagements are typically a single scoped application; enterprise engagements add governance, audit logging, and multi-team rollout. Both are covered under NDA from the first discovery conversation.