Skip to content
AI Implementations

Operationalize AI with confidence

We launch LLM & RAG programs that pair responsible governance with measurable impact—aligning use cases, data readiness, evaluation, and safety from day one.

  • LLM & RAG delivery
  • Evaluation & guardrails
  • Responsible AI ops
Explore an AI pilot See capabilities
AI operations team monitoring machine learning dashboards.
Proof in numbers

AI that scales responsibly

Every engagement balances experimentation with production readiness so teams see value fast without sacrificing safety.

6 weeks average time from pilot kickoff to live users
98% target adherence to guardrail policies post-launch
3x increase in evaluated prompts per sprint
Engagement blueprint

From ideation to trusted operations

Pods blend product, data, ML, and security expertise. We refine use cases, wire telemetry, and hand off runbooks your teams can own.

  1. 01 — Discover

    Map business goals, policy constraints, and success metrics while aligning stakeholders.

  2. 02 — Build

    Stand up data pipelines, orchestrate LLM/RAG components, and codify evaluation harnesses.

  3. 03 — Operationalize

    Roll out governance workflows, monitoring, and retraining playbooks so AI stays reliable.

Make AI useful, safe, and auditable

Use-case first

Co-design with business owners to target measurable workflows before training or tooling begins.

  • Pilot charters with success metrics
  • Human-in-the-loop validation paths
  • Value stream mapping for automation
  • Change management that sticks

Data readiness

We assess data quality, governance, and access controls so LLMs stay trustworthy and compliant.

  • Source inventory and lineage
  • Quality and bias guardrails
  • Role-based access enforcement
  • Retention and residency controls

Evaluation & observability

Continuous evaluation frameworks keep responses reliable, safe, and cost-efficient as usage scales.

  • Eval harnesses with real-world data
  • Bias, toxicity, and accuracy scoring
  • User feedback integrated into retraining
  • Cost and latency instrumentation

Safety & privacy

Policy alignment, red-teaming, and governance frameworks ensure AI delivers responsibly.

  • Policy mapping to regulatory obligations
  • Red-teaming for high-risk prompts
  • PII protection and masking patterns
  • Evidence trail for audits and reviews
Responsible pilots

Prototype quickly. Prove value responsibly.

Partner with Azul Computing to run an AI pilot backed by governance, evaluation, and a clear path to production.

Explore an AI pilot