BUILD
Data Engineering & Integration The foundation every successful AI project stands on.
How it runs
- 01Assess
- 02Design
- 03Build
- 04Hand over or operate
01The problem
Most AI Projects Don't Fail at the Model. They Fail at the Data.
The data an AI system needs is usually scattered across legacy databases, SaaS tools, spreadsheets, shared drives, and decades of scanned documents. It's inconsistent, duplicated, and often full of sensitive information that can't simply be copied somewhere new.
Teams that skip this work end up with AI that gives confident but wrong answers, pipelines that break every time a source system changes, and compliance questions nobody can answer.
We build the foundation first — clean, governed, well-documented data that your AI, analytics, and reporting can all rely on.
02How it works
How It Works
- 01
Assess
We map your data sources, quality issues, volumes, and sensitive fields, and agree the target use cases — AI, analytics, or both.
- 02
Design
We design the target architecture: ingestion, storage, transformation, access control, retention, and lineage.
- 03
Build
We deliver pipelines and models in short iterations, with automated tests and data-quality checks at every step.
- 04
Hand over or operate
Full documentation and runbooks for your team — or ongoing monitoring and support from ours.
03Deliverables
What We Build
- Data pipelines and ETL/ELT (batch and streaming)
- Warehouses and lakehouses on AWS, Azure, or Google Cloud
- Document processing at scale: OCR, extraction, classification — the feedstock for RAG
- Data quality, deduplication, and master-data cleanup
- Compliance-aware design: PHI/CJI segregation, encryption, retention, audit trails
- Integration with the business systems you already run
04Who it's for
Organizations with an AI or analytics initiative held back by messy data, siloed systems, or document archives that aren't machine-readable yet — from fast-growing companies to large enterprises and public agencies, especially in insurance, financial services, healthcare, legal, and public safety.
05Why LTK Soft
- 01We fix the data first — or tell you honestly that you're not ready yet.
- 02Compliance-aware data architecture: PHI/CJI segregation, encryption, retention, and audit trails designed in from day one.
- 03AWS Partner Network member — and equally at home on Microsoft Azure and Google Cloud.
- 04Experience with large data volumes, from insurance claims documents to market-data platforms.
- 05Your data stays in your own cloud account, under your control.
06Engagement
How engagements work
How it's scoped
Fixed-scope phases or a dedicated team
Scoped after a free call about your data sources and goals. Often combined with an AI build or a readiness assessment.
07FAQ
Questions we hear most
08Keep exploring
Related services
Talk Through Your Data Foundation
We'll assess whether your data is AI-ready — or what needs to happen first.