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.
We build a pipeline that centralizes logs from your applications and infrastructure, parses them into structured fields, and makes them searchable with retention and alerting. Debugging and audits stop meaning SSH-ing into servers.
We build a data flow that enriches your business data with outside information — weather, holidays, demographics, foot traffic — joined to your records for richer analysis and forecasting. Your models gain context they never had.
We help you give each team ownership of its own data, published as data products with their own data flows, agreements and access points, connected through shared standards. Each team owns its data as a governed product.
We build a pipeline that normalizes transactions across currencies, applying correct exchange rates by date and producing consolidated financials in your reporting currency. International operations roll up correctly.
We set on-time promises for your data and watch when each data load arrives, alerting the right people when data is late. Your team gets clear commitments and early warnings, not surprises, about when data is ready.
We aggregate your sales, fees, payouts, and returns from every marketplace you sell on into one normalized dataset, reconciling each platform's quirks. You see true unit economics across channels in one place.
We build the pipeline that prepares clean, gap-filled, feature-rich time series and serves them to forecasting models, then stores and monitors the forecasts. Demand, revenue, or capacity forecasts run on a dependable data foundation.
We integrate your field technicians' mobile app with dispatch, inventory, and billing so jobs, parts used, and time logged sync automatically even with spotty connectivity. Office and field stay in step without paperwork.
We build a Data Vault 2.0 model — hubs, links, and satellites — giving you a highly auditable, agile warehouse foundation that absorbs source changes and preserves full history. It suits regulated, fast-changing environments.
For teams whose live data double-counts orders or clicks when events are retried or replayed. We add duplicate blocking to your live data stream so each event is counted once, even at high volume. AI tracks the duplicate rate and explains spikes.
For businesses whose dashboards load slowly and show different numbers for the same thing. We build the tidy tables, summaries and metric layer behind your dashboard tool, connect it, and check every report. AI answers questions about your numbers in plain words.
For teams adding new data sources often and writing custom code each time. We build a reusable framework so any new source lands in your data lake the same way, with layout, schema and records captured, by filling a short setup file. AI drafts the setup for each new source.
We build a Customer 360 model that joins every interaction — orders, support, marketing, product usage — into one unified customer view with computed lifetime value, health, and stage. Every team queries the same complete picture.
We build robust backfill tooling for your pipelines so you can safely reprocess historical data for a date range or fix a bad load without corrupting downstream tables. Recovery from a bad day becomes a routine command.
We build an integration that pulls communication and meeting data from email and calendar into your CRM and warehouse, linking interactions to accounts and deals. Relationship activity is captured without manual logging.
We build a service that enriches your records with third-party data — company size and industry, the tools they use and public company-registry data — calling providers efficiently with caching and fallback across sources. Thin company records become complete.
We audit an existing warehouse for schema debt, unused tables, redundant models, broken lineage, and slow queries, then deliver a prioritized remediation plan with the quick wins already applied. You learn exactly what to fix and why.
For teams whose data lake only updates overnight and slows down with tiny files. We build a continuous feed that lands events in analytics-ready tables, tidying files and partitions as data arrives. AI watches file health and explains slowdowns.
We integrate your payment processors into a unified data layer that normalizes charges, refunds, disputes, and fees across providers into consistent transaction records. Finance analyzes payments across processors as one dataset.
We refactor a tangled, monolithic pipeline into modular, reusable, well-tested components with clear boundaries and documentation. Future changes touch one small piece instead of risking the whole chain.
For software companies whose customers share one database and need proof their data is kept apart. We design and build separation so each customer's data is only reachable by that customer, in the database and the data flows. AI runs regular separation checks and reports per-customer usage.
We convert full-refresh warehouse models to incremental processing, so each run only handles new or changed data instead of rebuilding everything. Runtimes and costs drop sharply while results stay correct.
We deploy a schema registry that governs every analytics and streaming event's structure, versioning schemas and enforcing compatibility so producers can't ship breaking events. Consumers rely on stable, documented contracts.
We add robust conflict resolution to a two-way sync where both systems can edit the same record, defining deterministic rules and merge strategies so concurrent edits resolve predictably. The dreaded sync loop and overwrite problems end.
We build disaster recovery for your data platform — automated backups, cross-region replication, and tested restore procedures so a failure doesn't mean permanent loss or days of downtime. Recovery is drilled, not theoretical.
We build a streaming pipeline that enriches live events by joining them against reference data and other streams in real time, so each event carries full context as it flows. Downstream consumers get enriched events, not raw fragments.
We integrate your membership, access-control, and billing systems so that a member's payment status automatically governs their door, app, and class access in real time. Lapsed members lose access and paid members' access is restored automatically when payment clears.
We build an ongoing data-quality scorecard that measures completeness, accuracy, consistency, and timeliness across your key datasets and reports trends to stakeholders. Data health becomes a managed, visible metric.
We migrate data into a new ERP, profiling and cleansing the source first — deduplicating, standardizing codes, and fixing broken references — so the new system starts clean. We validate every module's data post-load.
For factories whose machine data is stuck on the shop floor. We safely bridge your machine controllers and supervisory systems to your business data platform, so production data reaches dashboards without disrupting operations. AI flags machine stoppages and data gaps in plain words.
We wire a circuit breaker into your reporting so that if upstream data is stale or failed quality checks, dashboards show a clear warning or hold the last good data instead of silently displaying wrong numbers. Bad data never poses as truth.
We build a service that packages large datasets on demand or schedule and delivers them securely to partners or clients in their required format, with encryption, manifests, and delivery confirmation. Recurring data handoffs run themselves.
We build a data flow that turns deeply nested JSON or XML from APIs and logs into flat, easy-to-query tables while keeping how the records relate. Analysts query complex data with plain SQL.
We write your entire data setup — warehouse, data flows, permissions and connectors — as code, so environments can be rebuilt, reviewed and recovered after a disaster. Spinning up a new environment is a single command.
We build a pipeline that unifies appointment, reminder, and outcome data across your systems to compute no-show rates and risk factors by segment, time, and channel. You learn what drives no-shows and where to intervene.
We stream database changes directly into a search engine index so your app's search stays in sync with the source of truth in near real time. New and updated records become searchable within seconds without batch reindexing.
We instrument your data platform to attribute compute and storage costs to specific pipelines, teams, and datasets, so you know exactly what each workload costs. Waste becomes visible and chargeback becomes possible.
For online businesses that want their site or app to react to what a visitor just did. We build the data layer that keeps an up-to-the-moment profile for each visitor and feeds it to your site so content and offers adapt right away.
We set up a right-sized cloud data warehouse for a smaller business — connecting your handful of core tools, modeling the essentials, and wiring a dashboard, without enterprise overkill or cost. You get real analytics affordably.
We integrate your listing sources, portals, and CRM so property data, availability, and leads flow consistently across all of them without double entry. A change in one place propagates everywhere it should.
We build a pipeline that collects, labels, versions, and validates datasets for training your machine-learning models, with quality checks and dataset lineage. Model teams get reproducible, trustworthy training sets on demand.
We build the pipeline that computes cohort and retention curves from your user or customer activity, handling cohort definitions, activity windows, and retention math consistently. Growth teams see true retention by cohort.
We build a self-service portal where your clients or partners upload their data in any common format, which is validated, mapped, and ingested into your systems automatically with clear error feedback. Client data onboarding stops being a support burden.
For businesses that need to know the moment something goes wrong, not in tomorrow's report. We watch your live numbers and send one clear alert within seconds when something is off.
For companies whose key records still live on an old mainframe or AS/400. We read the old file formats, decode them correctly, and stream the records into a modern database your team and tools can use, kept up to date daily.
For companies counting events live, like ad clicks, orders or device readings. We build live counting that puts late and out-of-order events in the right time window, so your live numbers match the final numbers.
For companies moving off an old data warehouse. We move your data to a modern setup in your cloud, run old and new side by side, and produce a match report proving the new numbers equal the old ones before you switch.
For suppliers that must exchange orders, invoices and shipping notices with big retailers by EDI. We connect your ERP or warehouse system to each trading partner, turning their orders into yours and sending your shipping notices back in their format.