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End-to-End AI Services

From boardroom strategy to production deployment, we cover every phase of the AI lifecycle.

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01

Strategy

Plan your AI investment with confidence.

We work with leadership to define a clear AI strategy tied to measurable outcomes — not a slide deck that collects dust.

What's Included
  • AI opportunity assessment
  • Prioritized use-case backlog
  • Build vs. buy analysis
  • Data readiness report
  • 12-month implementation roadmap
Who It's For
Boards and C-suites evaluating AI's role in their 3–5 year strategy. Companies that have run pilots but lack a coherent AI narrative.
Outcome
A board-ready AI strategy, ranked use cases with ROI estimates, and a roadmap your team can actually execute.
02

Engineering

Build production AI, not just demos.

Custom ML models, LLM systems, and production pipelines, including natural-language agents like Text2MQL. Built for your domain and deployed into your infrastructure.

What's Included
  • Custom model development & training
  • LLM agents and natural-language query interfaces, such as Text2MQL
  • RAG pipelines and LLM integration
  • MLOps setup (CI/CD, monitoring, retraining)
  • Documentation & team handoff
Who It's For
Product and engineering teams who have identified an AI use case and need specialists to design, build, and ship it.
Outcome
A production-grade AI system integrated into your infrastructure, with automated pipelines and clear performance benchmarks.
03

Data Platform

Turn raw data into decision-making fuel.

Data engineering, analytics, and knowledge systems, including self-hosted workspaces like Strata, that make your AI accurate, auditable, and fast.

What's Included
  • Data architecture design
  • ETL/ELT pipeline development
  • Data quality & governance frameworks
  • Self-hosted notebook and SQL workspaces, such as Strata
  • Knowledge graph and vector store setup
Who It's For
Data teams who need to modernize their stack before deploying AI, or product teams whose models need cleaner, faster data.
Outcome
A data platform your AI systems can trust — with lineage, quality checks, and the throughput your use cases require.
04

Governance

AI that earns regulator and board trust.

Risk frameworks, compliance controls, and prompt screening like Guardrails, baked into your AI systems from day one, not bolted on after audit.

What's Included
  • AI risk and impact assessments
  • Bias testing and fairness audits
  • Regulatory compliance mapping (EU AI Act, GDPR, CCPA)
  • Audit trails and prompt screening with human review, such as Guardrails
  • AI policy and governance documentation
Who It's For
Organizations in regulated industries or any company deploying AI at scale that needs to demonstrate accountability to regulators, boards, or customers.
Outcome
An AI governance framework that satisfies regulators, earns stakeholder trust, and can be audited without scrambling.
How We Work

A proven methodology refined across many enterprise AI engagements.

  1. 01

    Discover

    We audit your data, processes, and objectives to identify the highest-value AI opportunities.

  2. 02

    Define

    Co-design the solution architecture, success metrics, and implementation roadmap.

  3. 03

    Design

    Build models, pipelines, and integrations, and prove their feasibility.

  4. 04

    Deploy

    Production launch with monitoring, documentation, and team enablement.

  5. 05

    Scale

    Ongoing optimization, capability expansion, and strategic review.

Most projects complete in 8–12 weeks.

Singa Lab · Enterprise AI

Not sure where to start?

Email us and we'll set up a free 30-minute discovery call. We'll tell you exactly which service fits your situation.

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