[Solutions · data engineering]
Connect operational and enterprise data into a governed foundation that teams can rely on, built through AI-accelerated data engineering practices that shorten delivery cycles and improve quality.
Less time chasing data, more time using it
Monitoring and reliability
Pipelines and DataOps
[Data Engineering Capabilities]
A strong data foundation is more than pipelines and platforms. We help enterprises connect data across systems, improve trust in information, and create a foundation that supports analytics, AI, and operational decision-making.
Strategy, architecture, and the pipelines that move the data
Define where data can create the greatest business impact, establish a practical roadmap, and prioritize initiatives that improve visibility, decision-making, and operational performance.
Design modern data platforms that connect structured and operational data, creating a reusable foundation for analytics, AI, semantic search, and enterprise knowledge discovery.
Connect operational and business systems into a unified data foundation that supports real-time, near-real-time, and historical analysis.
Trust, govern, and run the data in production
Identify quality issues earlier, improve transparency, and give teams confidence in the information they use every day.
Ensure data platforms remain reliable, scalable, and cost-effective through automation, monitoring, and operational best practices.
Establish clear ownership, consistent business definitions, and governed access so teams can use data confidently without compromising security or compliance.
[The Outcome]
Done right, cloud is not a hosting bill, it is operating advantage: lower cost, higher reliability, and a data foundation the rest of the business builds on.
Reliability
Reliable pipelines managed through DataOps practices
trust
Quality, lineage, and access controls built into the foundation
latency
Data available when decisions need to be made
Foundation
Trusted source of data across systems, plants, and business functions
[Who We Work With]
Data initiatives impact business leaders, data teams, and operational users alike. Our approach is designed to support each stakeholder while creating a foundation everyone can rely on.
[For the C-Suite]
Create a consistent foundation for analytics, planning, AI, and decision-making across plants, products, and business functions.
[For the CDO & Head of Data]
Establish the platforms, processes, and operating model required to manage enterprise data confidently and support future growth.
[For Business & Operations Leaders]
Give teams access to trusted, analytics-ready information that supports faster decisions and reduces manual reconciliation across systems.
[Continue Reading]
Manufacturing data is not just back-office tables. It is plant data from MES, ERP, and historians; sensor and IoT streams from the line; OT data with strict latency and reliability requirements; and unstructured data from quality, safety, and maintenance records. Ascentt builds pipelines and platforms for that reality, treating plant connectivity, streaming throughput, and operational continuity as first-class requirements rather than afterthoughts.
Both, plus the cloud-native data services that fit your estate. Ascentt engineers on Databricks for lakehouse and unified analytics workloads, on Snowflake for warehouse-led patterns, and on AWS and Azure native services where they fit the use case. The platform choice follows your existing investments and the workload, not a fixed preference.
Quality checks, lineage, observability, and a governed catalog are engineered into the pipeline from the first ingestion, not added afterwards. Every dataset has an owner, a definition, and a quality contract; every transformation is traceable; and every consumer sees only sanctioned data through role-based access. Governance is the foundation, not an audit afterthought.
We specialize in manufacturing and automotive organizations seeking measurable operational and business outcomes through AI.
Yes. Ascentt builds on the data lake, warehouse, and pipeline tooling your enterprise already runs. The work modernizes what is worth keeping, replaces what is not, and integrates with sources like SAP, MES, ERP, historians, and in-house applications without forcing a rip-and-replace.
[Continue Reading]
Our AI advisory engagements are designed for senior leaders in manufacturing and automotive enterprises who are tired of AI pilots that never reach production and ready to own a measurable outcome inside one quarter.
Solutions · BUILD
The cloud the data platform runs on, migration, modernization, and ongoing operations as one practice.
Solutions · think
Use your cloud & data foundation to improve forecasting, reliability, quality andoperational performance through machine learning.
Solutions · think
Turn cloud data into trusted business decisions through governed analytics, operational visibility & natural-language access to information.
