Enterprise AI engineering, end to end
Each engagement is scoped around a clear outcome — from first architecture decision to a system running in production.
AI Strategy & Architecture
A clear, technically grounded roadmap for where and how AI creates value in your organization.
Typical engagement — 2–4 week strategy sprint, typically followed by a phased implementation engagement.
What we do
- Assess current data, infrastructure, and team readiness for AI adoption
- Define target architecture across models, orchestration, and integration points
- Prioritize use cases by feasibility, risk, and business impact
- Build vs. buy analysis across model providers and platform components
Outcomes
- A prioritized, de-risked AI roadmap
- Reference architecture aligned to enterprise constraints
- Executive-ready business case for investment
Agentic AI Systems
Autonomous and human-in-the-loop agents engineered for reliability, governance, and real operational impact.
Typical engagement — 8–14 week build, from workflow design through production deployment.
What we do
- Design multi-step agent workflows with tool use, memory, and planning
- Implement guardrails, approval flows, and audit trails for autonomous actions
- Integrate agents with internal systems, APIs, and enterprise data
- Build evaluation harnesses specific to agent behavior and task success
Outcomes
- Agents that complete real tasks with measurable reliability
- Governance controls suitable for regulated environments
- Reduced manual effort on well-defined operational workflows
Enterprise RAG & Search
Retrieval architectures that ground your models in accurate, current, enterprise-specific knowledge.
Typical engagement — 6–10 week build, scoped to one or more knowledge domains.
What we do
- Design chunking, indexing, and retrieval strategies suited to your data
- Implement hybrid search combining semantic and structured retrieval
- Build ingestion pipelines for structured and unstructured sources
- Tune relevance, latency, and grounding for production traffic
Outcomes
- Search and Q&A systems with materially higher accuracy
- Lower hallucination rates through better grounding
- Retrieval infrastructure that scales with data growth
Data & AI Platform Modernization
The data and infrastructure foundation that every reliable AI system depends on.
Typical engagement — Ongoing platform engagement, typically 3–6 months for initial modernization.
What we do
- Modernize pipelines, storage, and governance for AI-readiness
- Build model gateways, inference infrastructure, and internal AI platforms
- Establish access controls, lineage, and data quality standards
- Design for multi-model, multi-workload flexibility
Outcomes
- A governed, AI-ready data foundation
- Faster time-to-production for future AI initiatives
- Lower infrastructure and inference costs at scale
AI Evaluation & Observability
The measurement layer that turns AI from a leap of faith into an engineered, monitored system.
Typical engagement — 4–6 week setup, integrated into existing CI/CD and monitoring stacks.
What we do
- Build evaluation suites covering accuracy, safety, and task success
- Implement tracing, logging, and monitoring across model calls and agent steps
- Set up regression testing for prompts, models, and pipeline changes
- Establish cost, latency, and quality dashboards
Outcomes
- Confidence to ship changes without regressions
- Early detection of drift, failure modes, and cost spikes
- A shared, quantitative language for AI quality across teams
Experimentation Platforms
Infrastructure to test, measure, and compound the impact of AI-driven features and personalization.
Typical engagement — 6–8 week build, plus ongoing advisory as experimentation scales.
What we do
- Build A/B testing and feature flagging infrastructure
- Design personalization systems driven by AI-generated signals
- Implement statistically sound measurement frameworks
- Connect experimentation results back into model and product iteration
Outcomes
- Faster, evidence-based iteration on AI features
- Personalization that measurably improves engagement metrics
- A durable experimentation capability, not one-off tests
Not sure where to start?
Book a strategy call and we'll help you identify the highest-leverage place to begin.