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Data & AI

Data Platform Development

Bring your data together in one platform built around your business, for reliable reporting, faster analysis and AI you can trust, designed and built by a founder-led team.

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What you get with an Authect data platform

A data platform is the shared infrastructure that brings your data together: databases, warehouses and lakes, the pipelines that feed them, and the tools for analysis, governance and security on top. Done well, it becomes the place every team goes for answers.

We design platforms for scale and flexibility, so they can take on new sources, users and workloads without a rebuild. Intelligent automation keeps data flowing, and clear access rules let people retrieve and analyse what they need quickly, on their own.

Every platform is led by a senior engineer, with the founders involved from the first workshop. We're vendor-neutral, and the platform lives in your cloud accounts from day one, defined as code and documented for your team.

Our solutions

Data platform solutions we deliver

The right platform depends on your data, your users and how fast decisions need to happen. These are the building blocks we design with, often in combination.

  • Data warehouses

    A central, query-optimised home for structured and historical data, and the single source of truth for reporting and analysis across the business.

  • Data lakes and lakehouses

  • Cloud data platforms

  • Hybrid data platforms

  • Real-time data platforms

  • Digital adoption platforms

  • Integration platforms (iPaaS)

Service benefits

The value of a custom data platform for your business

  1. 01

    Data in one accessible place

    Structured, semi-structured and unstructured data from across the business is consolidated in one repository, so people stop hunting through systems and exports.

  2. 02

    Smarter decisions

    With clean, connected data in place, predictive models, data mining and real-time analytics become practical tools rather than one-off projects.

  3. 03

    More efficient operations

    Automated ingestion, transformation and processing replace manual data handling, cutting errors and freeing your team for analysis.

  4. 04

    Governance and security built in

    Central storage makes it easier to enforce standards, manage access, track lineage and meet regulatory requirements for the data you hold.

  5. 05

    Room to scale

    An architecture designed for growth absorbs new data sources, users and use cases as your business changes, without starting over.

  6. 06

    Easier collaboration

    Authorised users across the organisation can find and share trusted data, so teams build on each other's work instead of duplicating it.

How we work

How we develop and integrate data platforms

Four stages take your platform from requirements to production. You see working pieces early, and a senior engineer stays responsible for the architecture from start to finish.

  1. 01

    Planning and requirements

    We work with you to understand your data sources, users and business goals, then agree the outcomes the platform must deliver, its scope and a roadmap.

  2. 02

    Data modelling and architecture

    We turn requirements into conceptual and logical data models and an architecture: the components, technologies, security model and how data flows between them.

  3. 03

    Platform development

    We build, configure and integrate the storage, processing, pipelines and analytics tools in short iterations, defined as code and tested as we go.

  4. 04

    Deployment and maintenance

    After testing and validation against the agreed criteria, we launch the platform, train your team, and then monitor, tune and extend it as your needs grow.

Industries

Industry-specific use cases for data platforms

Healthcare

A central, secure repository for patient records, data for predictive analytics and disease prevention, support for clinical research, remote monitoring and telehealth data, and operational analytics that help hospitals run smoothly.

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Retail

Customer data consolidated for segmentation and personalisation, demand forecasting and stock optimisation, an omnichannel view of every order, supply chain visibility and real-time analytics for store operations.

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Media & Entertainment

Audience insight and segmentation, real-time analytics on streaming data, recommendation engines, ad targeting and monetisation, rights and licence management, and predictions of how content will perform.

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Fintech

Warehouses for financial reporting and analysis, automated risk and regulatory reporting, data for investment decisions, budgeting and forecasting, real-time transaction monitoring and asset and liability management.

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Insurance

Data-driven risk assessment and underwriting, faster claims processing, customer profiling and personalised services, predictive analytics for loss prevention and policy changes handled in real time.

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Logistics

One view of fleet, warehouse and order data, live shipment tracking, route and capacity planning, demand forecasting and the analytics that show where time and money are lost along the chain.

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Energy

Platforms for high-volume sensor and meter data, asset performance and predictive maintenance, consumption and generation forecasting, and the reporting that regulators and investors ask for.

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Why Authect

What distinguishes Authect's data platform development

  1. 01

    Software engineering at the core

    We build data platforms the way we build any serious software: designed with care, defined as code, tested, reviewed and documented, so they stay reliable as they grow.

  2. 02

    Strategy and data science in the same team

    The engineers who design your platform also understand data strategy and machine learning, so it's shaped by how the data will actually be used.

  3. 03

    Founders and a senior engineer on every project

    You work directly with the people who design and build your platform, never through a salesperson or a chain of account managers.

  4. 04

    Your platform, your accounts

    Everything we build runs in your cloud accounts, on tools you choose, with no proprietary layer that ties you to us.

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Technologies

The platforms and tools we build with

We're vendor-neutral. We recommend technology based on your data volumes, your team's skills, your existing contracts and what it will cost to run, and we explain the trade-offs so the decision is yours.

These are the tools we work with most often. If you've already chosen a platform, we build on it rather than replacing it.

Warehouses and lakehouses

  • Snowflake

    A cloud data warehouse that separates storage from compute, well suited to many teams querying the same data.

  • Databricks

    A lakehouse that combines data engineering, analytics and machine learning on open table formats.

  • BigQuery, Redshift and Microsoft Fabric

    The native analytics platforms on Google Cloud, AWS and Azure, a natural fit if you're already invested in one.

Pipelines and processing

  • dbt

    Tested, documented SQL transformations under version control, so data models change safely.

  • Apache Airflow

    Orchestration that schedules and monitors pipelines, with retries and clear visibility of every run.

  • Apache Kafka and Spark

    Streaming and distributed processing for real-time events and datasets too large for a single machine.

Insights

FAQs

Data platform FAQs

What is a data platform?

A data platform is the combined infrastructure for integrating, storing, governing and analysing an organisation's data. It usually brings together pipelines that collect data from your systems, a warehouse, lake or lakehouse to store it, and tools for transformation, analytics, machine learning, security and access control, so everyone works from the same trusted data.

Data warehouse, data lake or lakehouse: which do we need?

A warehouse suits structured data and fast, consistent reporting. A lake stores large volumes of raw and unstructured data cheaply. A lakehouse combines the two, adding reliable tables and governance on top of lake storage. Many organisations end up with a mix; we recommend what fits your data, workloads and budget.

Should we build a custom platform or use an off-the-shelf product?

Usually both. We build on proven managed services such as Snowflake, Databricks or your cloud provider's tools, and customise the data models, pipelines, security and integrations around your business. That gives you a platform that fits without reinventing what already works.

Can a new platform work with our existing systems?

Yes. Connecting to the systems you already run, from ERP and CRM to legacy databases and spreadsheets, is a core part of the work. Where data must stay on-premises, we design a hybrid platform that keeps it there and still makes it available for analysis.

How do you keep running costs under control?

We size compute to the workload, separate storage from processing where the platform allows, schedule heavy jobs sensibly and set up budgets, alerts and cost reports from the start. You see what each part of the platform costs, and why.

Tell us what you’re building. A founder replies within one working day, and builds it with you.

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