Your tools connected, so your numbers update themselves instead of being copied by hand.
For businesses whose data sits in many systems and gets copied into spreadsheets by hand. We build a scheduled pipeline that pulls from your databases and apps, cleans the data and loads tidy tables into one warehouse. AI watches each run and explains problems in plain words.
For companies whose reports run on fragile, undocumented data logic nobody dares touch. We move raw data into a clear landing area and rebuild your reporting tables as versioned, tested models with documentation. AI keeps the documentation current and explains each model's purpose.
For companies that need to react to what happens in their app or devices within seconds. We build a streaming pipeline that takes in events, combines them over short time windows and feeds fast results to your app or dashboards. AI watches the flow and explains delays or unusual spikes.
For companies whose reports slow down the main database or show yesterday's numbers. We set up a live copy that streams every new, changed and deleted record from your production database into your warehouse or a replica, without heavy queries on the original. AI watches the copy and explains any lag.
For companies with useful customer data in a warehouse that their sales and marketing tools never see. We push segments and figures back into your CRM, email and support tools on schedule, sending only what changed. AI explains sync failures and suggests field mappings.
We set up automatic data-quality checks that run on every data load, testing freshness, sudden changes in volume, missing values, duplicates and broken links between tables. Failures raise alerts and can stop bad data from reaching dashboards.
We stand up a searchable data catalog that documents every table, column, and owner, and traces column-level lineage from source through transformations to dashboards. Analysts find trusted data and see exactly what feeds any metric.
We build a bidirectional integration between your CRM and ERP so accounts, orders, invoices, and inventory stay consistent across both. The middleware maps schemas, resolves conflicts, and queues changes so neither system blocks the other.
We migrate data out of an aging system into a modern platform, profiling the source, mapping fields, transforming formats, and validating record counts and integrity after load. We run parallel dry-runs before the final cutover.
We design a clean analytics tracking plan and instrument your web and mobile app to emit consistent, typed events into your warehouse. Every event follows a governed schema so downstream analysis isn't guessing what a field means.
We build an MDM hub that unifies your core entities — customers, products, suppliers — into golden records with survivorship rules across source systems. It resolves duplicates, standardizes attributes, and publishes the trusted version back out.
For businesses whose customer information is scattered across store, email, ads and support tools. We bring it together into one profile per customer, linking their activity across devices and channels, and build segments you can send to your marketing tools. AI suggests segments and summarises customer behaviour.
For businesses building AI features like smart search, recommendations or assistants on their own content. We turn your text, images or activity data into searchable AI-ready form, store it in a vector database and feature store, and keep it refreshed. Your apps get one simple way to fetch it.
We synchronize inventory levels across your online store, marketplaces, and physical POS in near real time so a sale on one channel decrements stock everywhere. The engine handles rate limits, conflicts, and oversell protection.
For companies whose software talks to many outside services, each with its own quirks. We build a middle layer that handles logins, retries and limits for every provider and gives your apps one clean connection. AI watches errors and explains provider problems in plain words.
For companies with lots of data, such as logs, sensor readings or files, that is too costly to keep in a regular warehouse. We build a store on low-cost storage with reliable tables, history you can go back to, and a query tool. AI keeps tables tidy and explains query costs.
We design and build a dimensional (star-schema) model for your warehouse, defining conformed dimensions and fact tables that make analytics fast and intuitive. We handle slowly-changing dimensions so history is preserved correctly.
For businesses that rely on notifications from payment and software providers and occasionally lose them. We set up a receiver that checks each notification is genuine, removes duplicates, stores it safely and delivers it to your systems, replaying any that fail. AI watches deliveries and explains failures.
We audit your warehouse workloads and re-engineer them to cut compute and storage spend — right-sizing warehouses, clustering tables, pruning unused models, and rewriting expensive queries. We deploy the changes and monitor the savings.
For operations teams who want to see what is happening right now, not yesterday. We build the pipeline behind a live dashboard, streaming events through running totals into a fast store that keeps tiles current. AI writes short notes on unusual changes as they happen.
For businesses whose customer lists are full of duplicates from typos and different spellings. We build a matching engine that finds duplicate records and merges them by your rules, sending uncertain ones to staff. It keeps running on your own infrastructure so new duplicates do not creep back.
We stand up managed connectors that pull data from your key SaaS tools — payments, ads, support, CRM — into your warehouse on schedule with schema handling and incremental loads. New sources plug in without custom code each time.
For businesses with machines, vehicles or sensors sending readings all day. We build a pipeline that buffers readings, handles late or out-of-order data and stores it in summarised time-based tables. AI spots silent devices and unusual readings and explains them.
We implement Type 2 slowly-changing dimensions so your warehouse preserves the full history of records that change over time — prices, statuses, assignments. Every analysis can ask what a value was on any given date.
We implement role-based access, column-level security, and data masking across your warehouse so sensitive fields are protected and access follows policy. We document who can see what and keep a searchable access log.
We move a slow nightly data run to one that updates continuously, so data that used to arrive tomorrow arrives in minutes. We run both side by side and check they match before switching over.
We consolidate data from many branches, franchises, or stores that each run their own systems into one central warehouse with a common model. Local quirks are normalized so headquarters compares locations on equal terms.
We build an automated reconciliation pipeline that matches transactions across your payment processor, bank, and ledger, flagging mismatches and unexplained gaps. It runs daily and produces an exception report for finance to clear.
For teams with many data pipelines who only learn of failures when a report looks wrong. We track every pipeline's run time, freshness, volumes and failures on one dashboard with history. AI explains what broke and why, and routes alerts to the right person.
We take the critical spreadsheets your business secretly runs on and migrate them into a proper relational database with validation, relationships, and multi-user access. Formulas become queries and manual edits become a controlled app.
We build an automated pipeline that locates, exports, or deletes all data for a given individual across your systems when a privacy request your team has verified and approved comes in. It produces a verifiable record of what was found and actioned.
We build a pipeline that ingests product data from suppliers and internal sources, normalizes attributes and units, enriches with categories, and publishes a clean catalog to your storefronts. It handles feed formats and de-duplicates variants.
For companies where every report shows a different revenue or customer count. We define each metric once in one central place, so every dashboard and query calculates it the same way. AI answers questions about metrics and explains definitions in plain words.
We build the data model and data flow that link ad clicks, visits and sales into complete customer journeys, sharing the credit across every channel that helped. Marketing sees which spend actually drives revenue.
For growing apps whose main database is hitting its limits. We split data across several servers with a routing layer, keeping your app working the same way, and move live data without taking you offline. AI watches load and explains slowdowns.
We build a pipeline that produces masked or synthetic copies of production data for testing and analytics, masking identifiers while preserving statistical shape and referential integrity. Teams get realistic test data with far fewer identifiers in circulation (masked data is still handled under your own privacy policies).
We connect your POS systems to one central data flow that pulls sales, items and payments into the warehouse continuously, made consistent across terminals and locations. Retail analytics run on complete, up-to-date transaction data.
We build a pipeline that turns raw clickstream events into sessions, funnels, and paths, computing session boundaries and page sequences. Product and growth teams analyze how users actually move through your app.
We connect the systems along your order-to-cash process — storefront, fulfillment, invoicing, payment — so an order's full lifecycle flows automatically without manual handoffs. Status stays synchronized end to end.
For charities and schools with the same supporter entered several times across donation, event and CRM tools. We build a system that matches and merges duplicates while keeping every gift in the history, with unclear matches sent to staff. It runs on your own infrastructure to keep records clean.
We implement data contracts between the teams that produce and consume data, defining schemas and expectations that are enforced automatically in CI and at ingest. Breaking changes are caught before they hit downstream consumers.
We build a pipeline that ingests location data, joins it against geographic boundaries, and computes spatial metrics like territories, distances, and coverage. Location-heavy businesses get map-ready analytics tables.
We migrate your on-premise or legacy warehouse to a modern cloud platform, moving schemas, data, and transformation logic while validating parity at each step. We plan the cutover to avoid disrupting reporting.
We build a pipeline that turns your subscription and payment events into clean recurring-revenue metrics — MRR, churn, expansion, cohorts — reconciled against the billing system. Finance and leadership get trustworthy SaaS metrics.
For teams whose data pipeline changes sometimes break reports in production. We add tests, a staging area and automatic checks so every change is validated before it goes live, with a clear roll-back. AI reviews each change and explains test failures.
We integrate your booking or reservation platform with your CRM, calendar, and accounting so every appointment flows through as a customer record, a schedule entry, and a revenue line. No detail gets re-typed across systems.
We build a system that automatically moves aged data from expensive hot storage to cheap cold tiers while keeping it queryable, applying retention policies per data type. Costs drop without losing access to history.
We build a data flow that takes in and standardizes data from new suppliers whatever their file format or field names, mapping each onto your own structure with checks. Onboarding a supplier goes from weeks to hours.