From the first architecture call to a live dashboard your operations team opens every morning — here is exactly how we get you there.
Step 1
We map where your numbers actually live — ERP, CRM, storefront, spreadsheets — and agree on the five metrics that drive decisions. You leave with a source-of-truth definition for each one, not a forty-page discovery deck nobody reads.
Step 2
We build the ingestion and data model that feeds everything downstream: secure API connections to Shopify Plus, NetSuite, SAP, or your Postgres, plus the transformation layer. This is the part our AI Automation Consulting engagements prove most teams skipped.
Step 3
Within two weeks you get a working BI dashboard on your real data — not a Figma mockup. It runs on the same architecture as our AI Analytics & Business Intelligence builds (Python, FastAPI, PostgreSQL, self-hosted Retool), so nothing gets thrown away later.
Step 4
We deploy inside your private cloud, wire in alerting, and train your team on the model so they can add reports without us. You own the repository and the data model outright — the same handover we ran on this margin-defense build.

By week two you are clicking through a live dashboard built on your own numbers. Underneath it, each component gets the right tool: classic engineering for the pipelines, AI for messy free text, low-code for the interface. If the data model is wrong, you find out in fourteen days — not after six months.
We have not published a case study labeled "business intelligence services" — but two shipped builds are the same work: a self-healing pricing and margin dashboard that returned 12% retained margin in six weeks, and a returns-analytics engine that turned 15,000 free-text notes into a ranked fix list worth $130K.

Every BI pipeline runs inside your private cloud perimeter, SOC 2 and GDPR-aligned. Your revenue, customer, and supplier data never leaves your environment and never trains a public model.
You own the repository, the data model, and every transformation we write. There is no proprietary BI platform or per-seat licence standing between your team and its own reporting layer.
No junior bench. Your build runs with a data and analytics lead who spent five years building SAP Analytics BI solutions at Allianz Technology, a backend architect, and a solutions architect.
The warehouse and semantic layer are engineered for the volume you will have in three years, not just today. Adding a new source or report later is a change, not a rebuild.
$70,000+
A full analytics platform across several domains — finance, supply chain, retail — with AI layers on unstructured data and automated actions wired back into your systems of record. Built for companies replacing a stalled enterprise BI rollout.
What's included?
Everything in Production BI: extended across multiple business domains
AI Analytics Layer: LLM extraction from documents, notes, and free text
Closed-Loop Automation: insights trigger actions in your ERP or storefront
Compliance & Governance: SOC 2/GDPR-aligned controls and human approval gates
You could hire a freelance BI contractor, brief an offshore team, or buy a platform licence — or work with one team accountable for the reporting outcome.
Pipelines get classic engineering, unstructured data gets AI, dashboards get low-code — the right approach for each component, not the same hammer for every nail.
A single team of solutions architects, data engineers, and analysts owns your BI build from audit through handover — no contractor relay race.
Our packages start at $15,000, not the six-figure floor and nine-month rollout that enterprise BI suites quote a 200-person company.
No proprietary platform, no per-seat licence, no subscription standing between your team and the reporting layer after the engagement ends.
Engaging us for business intelligence services follows the same four-stage rhythm whether you are a 30-person e-commerce brand or an operations team inside a larger company — fast enough to see value in weeks, disciplined enough to hand to your engineers later.




The same modeling discipline applies across the verticals where we already run production systems — retail brands watching margin by SKU, procurement teams tracking supplier spend, and finance teams closing the books without a week of manual reconciliation.
A quarter spent on stale spreadsheets is a quarter a competitor spends acting on live numbers. Book a free architecture audit — you will speak with a solutions architect, not a sales rep, and leave with a data model sketch.
A working dashboard on your real data is usually live in about 14 days. A full production business intelligence layer — multiple sources, modeled warehouse, private-cloud deployment, team training — typically runs four to eight weeks depending on how many systems we connect and how clean the source data is. You see something usable long before the engagement ends.
Our BI Pilot Dashboard starts at $15,000, a full Production BI Build at $38,000, and a multi-domain Enterprise BI & Automation engagement at $70,000. That is project cost with a defined end, not a per-seat licence that grows with headcount. Most SMB and mid-market clients start with the pilot and expand once the numbers justify it.
Yes — the repository, the data model, the transformation logic, and the dashboard definitions are yours. We deploy into your cloud account and hand over documentation at the end. If you later want to move the whole business intelligence layer in-house or to another vendor, nothing proprietary is holding it hostage.
Every pipeline and model runs inside your own private cloud perimeter under SOC 2 and GDPR-aligned practices. Your financial, customer, and supplier data does not leave your environment and is never used to train public models. Where we use frontier LLMs on unstructured text, we deploy them within that same perimeter with logging you can audit.
Yes. We build direct API connections to SAP, NetSuite, Coupa, Shopify Plus, Amazon Seller Central, Magento, and standard PostgreSQL or SQL Server estates — no rip-and-replace. If you already own Power BI or Tableau licences, we can model the warehouse underneath them instead of replacing your front end. The integration layer is classic, tested software engineering, not an LLM guessing at your schema.
No retainer is required. Your team is trained on the data model and can add reports and sources without us. Some clients keep a light support arrangement for new integrations or model changes; others take the system fully in-house. Either way, the business intelligence layer keeps running because you own the deployment, not because you keep renewing a contract.