Data you can trust,
AI you can use

Nuronest fixes the foundations and ships AI your teams actually adopt. We bring order to your data, then deliver assistants, automations, and alerts that make everyday work faster and more reliable. Small, senior, and hands‑on—you work directly with the people who deliver.

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What we do

Data Fundamentals

Your decisions are only as good as the data behind them. We make that data dependable and easy to use—without turning your stack upside down.

What this includes: clear definitions and shared metrics, tidy pipelines with observability, simple data checks so numbers stay trustworthy, and documentation people can actually find.

Signals you can show to a CTO: semantic model/metric layer, data contracts & tests, orchestration that teams keep (e.g., Dagster), SQL-friendly models (yes, we write them).

AI Implementations

Once the basics are solid, we turn them into visible gains. Think plain-language answers, workflow copilots that remove repetitive steps, and proactive alerts when something drifts. Everything is explainable, permission-aware, and built in your stack.

What this looks like: a question in everyday language → an auditable query and a clear answer; routine tasks automated; notifications when thresholds are crossed—no black boxes.

Proof of work

Concise snapshots you can share.

Snapshot A — “Talk to the Data”

Before: Teams waited days for answers or wrote ad-hoc SQL.

After: People ask in plain language and get answers they can trust—plus the option to see the underlying query. Definitions are consistent, and the backlog shrinks.

We did: introduced a business vocabulary (semantic layer), synced metadata so it stayed fresh, added change alerts, and shipped a simple interface that plugs into the warehouse.

Example impact: reporting time down [30–60%] in the first domain; clearer decisions in [N weeks].

Snapshot B — “Master Data Without the Mess”

Before: “What is a customer?” changed by team and system; breakages after every schema tweak.

After: One set of agreed definitions and stable downstream views for analytics and operations.

We did: built a wide core model that handles real-world complexity, then exposed guided views that are easy to use and hard to misuse.

Example impact: fewer reconciliation fights, fewer broken dashboards, faster onboarding for new analysts.

How we work

Working model

  • Choose a high-value slice. We define success and pick one area (e.g., service, finance, operations).
  • Prove it fast. We tighten the data, ship one AI use case, and measure the impact.
  • Scale without drama. We expand to the next teams, with training, docs, tests, and ownership that stays with you.

Why Nuronest

Small by design. Senior by default. Fewer slides, more pull requests. Built in your cloud and repo. Explainable by design—no mystery models.

Let’s talk

Tooling familiarity

SQL Server • Python • Polars • Dagster (and we adapt to yours)