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THE NYCG / Data & Integrations

Data lakes, pipelines & systems integration

Make the right information available to your applications, analysts and AI systems. We scope the data sources, movement, storage and access around what your team needs to do.

Discuss your data project

What we can help with.

Explore the work and the deliverables we can scope together.

Data lakes & data foundations

Bring information from different sources into a structure your team can use and maintain.

Possible deliverables
A defined data architecture and ingestion scope, with ownership and access decisions.
Technical scope
Work to scope
Source inventory, storage design, ingestion, data organization and access requirements for a lake or warehouse.

Pipelines & data quality

Move data between systems and make missing, duplicated or outdated records easier to find.

Possible deliverables
A tested pipeline with quality checks, run visibility and a recovery procedure.
Technical scope
Work to scope
Batch or event-driven pipelines, transformations, validation, reconciliation and recovery from failed runs.

APIs & application integration

Let existing applications exchange information and complete a connected workflow.

Possible deliverables
Documented interfaces and tested connections between the agreed systems.
Technical scope
Work to scope
API design, webhooks, field mapping, identity and permissions, duplicate protection and action receipts.

Prepare knowledge for AI

Give a search or AI application access to relevant information with a clear path back to its source.

Possible deliverables
A knowledge pipeline and retrieval tests tied to the questions your users ask.
Technical scope
Work to scope
Document intake, OCR, indexing, embeddings, retrieval and access-aware knowledge connections.
Explore your industry context

Your industry shapes the data, permissions and review process. These examples explain possible approaches; they are not client case studies.

Before we start

Your questions, answered.

Define the systems and constraints in your project brief
Do we need a data lake or a simpler integration?

Begin with who needs the information and what they need to do with it. Sharing records between two applications is a different scope from bringing many sources together for analysis or AI. We assess the sources, existing storage and access needs before proposing an architecture.

Can you connect data across existing applications?

Yes. We can scope APIs, webhooks or data pipelines around the available interfaces. The work includes deciding how records match, how often data moves and how to detect and recover from failed or incomplete transfers.

How can documents become useful to an AI system?

We can scope document intake, OCR, indexing, embeddings and retrieval as a connected knowledge pipeline. The result needs a path back to its source, appropriate access permissions and retrieval tests based on the questions your users actually ask.

How do we discuss personal or confidential data?

Start by describing the data categories and who should be able to access them. We can scope permissions, handling requirements and boundaries for connected tools with your team. Keep personal records, credentials and confidential documents out of the initial website enquiry.

Start a conversation

Bring the problem.
We’ll work through it.

A rough description is enough. If you have technical requirements, bring those too.

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