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Your agents are only as good as the data you let them see

A unified, secure, governed data foundation on AWS — Lake Formation, governed lakehouses, and access controls fit for regulated industries. The platform every other AI solution sits on.

AWS-native or Databricks
THE PROBLEM

The Challenge

Data foundation problems split into two shapes — treating them as one is why most projects under-deliver. SMBs fragment data across 20+ tools. Regulated industries know where data is — they just can't prove who's touched it.

1

Twenty databases — none talking

Data everywhere. Operational systems, CRMs, finance tools, spreadsheets. One overworked analyst holds the institutional memory. Analytics slow, ad hoc, impossible to delegate.

Fix

The fix is a unified data lake — S3 as golden landing zone, Glue crawlers to infer schema, Athena to make it queryable. The analyst stops being a single point of failure.

2

The data's there. Governance isn't

You know where the data lives. You don't know who's read it, when, or whether the access pattern would survive an audit. AI agents amplify that problem.

Fix

Lake Formation fine-grained permissions, row-level access controls, and a full audit trail are the answer. Every read attributable. The security conversation ends with 'yes'.

3

Agents can't plug in

Every other AI solution — agentic builds, productivity tools, fine-tuned models — assumes a clean, governed, accessible data foundation. Without one, every build delays on the same data conversation.

Fix

The data foundation is the platform everything else stands on. Build it once, correctly, and every downstream AI project gets faster. Skip it, and every project pays the debt.

HOW WE ENGAGE

How We Deliver

01Phase

Discovery & architecture design

Weeks 1–3

Understand your data landscape, integration needs, and governance requirements. Design the foundation before implementation.

  • Data inventory — what sources, what formats, what quality, what volume
  • Integration assessment — frequency, latency requirements, transformation complexity
  • Governance scoping — regulatory requirements, access control model, audit needs
  • Architecture design — Lake Formation, governed lakehouse, or hybrid approach

Output

Architecture agreed and signed off by your infrastructure and security teams.

02Phase

Foundation build & integration

Weeks 4–8

Lake Formation setup, governed access controls, data ingestion pipelines, and audit trail wiring. Data unified and queryable.

  • S3 data lake structure and lifecycle policies
  • Glue data catalogue and schema inference
  • Lake Formation fine-grained access controls and data permissions
  • Data ingestion pipelines — batch and real-time where needed
  • Athena workgroup setup and query optimization

Output

First queries run successfully and data governance is enforced.

03Phase

Governance & handover

Weeks 9–12

Standing access control framework, data lineage documentation, and operational runbook. Your team owns it.

  • Access control framework — roles, policies, approval workflows
  • Data lineage documentation — where data comes from, how it's transformed
  • Operational runbook — how to add new sources, manage retention, handle incidents
  • Monitoring and alerting — data freshness, pipeline health, access anomalies

Output

Your team can operate the foundation independently. Runbook complete and signed off.

WHAT YOU GET

What You Get

🎯

Unified data lake: S3 as your golden source. Glue crawlers infer schema. Athena makes it queryable. Your analyst stops being a single point of failure.

🔐

Governed access: Lake Formation fine-grained permissions. Row-level access controls. Full audit trail. Every read attributable. The security conversation ends with 'yes'.

Every agent can plug in: The platform every other AI solution stands on. Build it once, correctly. Every downstream project gets faster. Skip it, and every project pays the debt.

🚀

No data conversation delays: Your team owns the foundation. Data's clean, governed, and ready. AI projects start with the model, not the data debate.

ENGAGEMENT SHAPES

Choose Your Engagement

SMB unification

Data Lake

Unified lake, data pipeline, and analytics setup. Lightweight governance for growth.

  • Unified data lake on S3
  • Glue data catalogue setup
  • Athena analytics layer
  • Basic governance framework

Cost

Fixed fee

Duration

4–6 weeks

Most commonRegulated enterprises

Governed Foundation

Lake Formation, fine-grained access, audit trail, and compliance framework. Production-ready.

  • Lake Formation setup
  • Fine-grained access controls
  • Audit trail wiring
  • Compliance framework

Cost

Fixed fee

Duration

6–10 weeks

Ongoing

Standing Programme

Ongoing governance, monitoring, and optimization of your data platform.

  • Access control management
  • Data pipeline monitoring
  • Governance reviews
  • Optimization recommendations

Cost

Monthly retainer

Duration

Monthly

Not sure which one fits?Book a discovery call
WE'VE DONE IT BEFORE

Related success stories

CONTACT US

Ready to build a data foundation for AI?

Let's unify your data and govern access so every AI project moves faster.

Why talk to us:

Outcome-driven recommendations

AWS-recognised delivery expertise

Risk-aware AI adoption

Clear next step, not a sales pitch

Start with a focused 20-minute conversation about your goals — no pressure, no commitment.