U.S. Power BI & Data Studio
Slow dashboards, refreshes that fail overnight, three different numbers for the same KPI. That's almost never a chart problem — it's the model underneath, and it's what we rebuild. We also build the AI that reads the documents your team has no time to read, and scores them with a written reason. And because talk is cheap: nine apps live on the App Store, built and maintained by us.
Client · LicitaSmart
“We were reading tenders by hand and losing opportunities to sheer volume, not for lack of interest. The engine Summitview built extracts 23 to 24 documents per tender, where the tool we used before found 3. And opportunity matching went from zero useful hits in 3,000 to dozens a week.”
What you buy
Every one of these has a fixed shape: a name, a length, and a list of what lands in your hands at the end. Scope and price are agreed before we start, and we don't bill by the hour — if we underestimate, that's our problem, not yours.
In one week you know why the report is slow, and what fixing it costs.
What you get
Yours to keep and act on, with us or without us. It's a product, not a sales call.
See a full sample report →
The report opens in seconds, the refresh stops breaking, and the number becomes one number.
What you get
Quoted after the diagnostic, so the number is real — not a guess with a change order waiting behind it.
Talk about a rescueWe take 50 of your documents and show you, measured, how much the AI actually gets right.
What you get
The same engine that runs in production inside LicitaSmart: 23–24 documents extracted where a commercial LLM found 0–3.
Talk about a pilotYour systems start talking to each other, and the number is ready before you are.
What you get
Sized on how many systems feed it. That's the one thing we scope before quoting.
Scope a buildThe capability of a data department without hiring one.
Cancel in any month and keep everything — the models, the code, the documentation. We don't build dependencies on purpose.
Talk retainerWhy trust us with your stack
A consultancy asking for access to your database should be able to show you something it built and still keeps running. Everything below was designed, engineered, secured and shipped by us, and is live today — you can download it before you talk to us. The data work we do for clients sits behind an NDA; this is the part we can prove in public.
Our flagship data product. It ingests Brazil's public-procurement feed, matches every tender against a company profile, and scores the odds 0–100 with the reasoning attached — plus on-device document OCR. Data engineering, ML scoring and generative AI in one shipped system.
Vaccine schedules, prevention tracking, and an AI assistant with strict medical guardrails — built on encrypted, multi-tenant Firebase. Live on the App Store.
Brand partnerships managed end to end for content creators: deliverables, deadlines, invoicing status, revenue tracking, and an AI brief-checker that flags a mismatch before the camera rolls.
A premium “liquid-glass” block puzzle with explosive combos, fair monetization, and zero pressure. Live on the App Store and Google Play.
A cottagecore merge-3 with an original 5×5 progression, AI-generated seasonal content, and a monthly drop pipeline most studios can't run.
Bake, merge, and rebuild a family bakery — calm, offline, no timers. Shipped to the App Store with full IAP and Season Pass billing.
Gallery-quality, AI-generated coloring art with a text-to-coloring-page pipeline running in production. Live on the App Store.
A fresh murder case every morning, five suspects, one liar. Hand-verified logic — every case is solvable, which is more than most AI-generated mystery apps can say.
A protein tracker with a virtual pet that thrives or wilts on your intake — purpose-built for GLP-1 and post-bariatric users, where missing protein is a clinical problem, not a vanity one.
“Anyone can promise you an app.
We hand you a track record — products on the store, systems in production, and metrics you can verify before you sign a thing.”
What we fix
It usually starts the same way: someone adds a visual, then a measure, then another table — and two years later the report takes four minutes to open, the refresh fails on Sunday night and finance keeps its own spreadsheet anyway. Almost none of that is fixed in the chart. We rebuild it at the semantic model: grain, star schema, one definition per metric, DAX that survives contact with reality. Then, if you want it to stay fixed, we stay on as your fractional data team — the capability of a data department without the headcount.
We audit the model you already have and tell you honestly whether it's worth repairing or rebuilding — most of the time it's repairable. Star schema, grain fixed, duplicated measures collapsed, row-level security, and a refresh that stops failing silently. Dashboards an executive reads in ten seconds, not ten minutes.
Messy operational data turned into clean, trustworthy datasets. We model facts and dimensions, define each metric exactly once, and end the “three different numbers for the same KPI” meeting for good.
Not a chatbot demo. AI that opens the PDF, pulls what matters, ranks it and returns a score with the reason written out, so a human can audit the decision instead of trusting a black box. Running in production inside LicitaSmart: 23–24 documents extracted where a commercial LLM found 0–3, and a matching engine that went from zero useful hits in 3,000 to dozens a week. Useful wherever someone reads documents to decide — tenders, contracts, compliance, cross-border trade, inspection.
ETL/ELT that runs unattended: SSIS, Azure Data Factory, Python and Celery — scheduled, monitored, and alerting you when a source system breaks, before your Monday meeting does it for them.
Schema design, indexing strategy, query tuning, migrations, and cost control across SQL Server, Azure SQL and PostgreSQL. When a report takes four minutes, that's a modeling problem wearing a hardware costume — we fix the cause.
Forecasting, segmentation, propensity scoring, classification, anomaly detection. Models trained on your data, validated honestly — including when the honest answer is “this signal isn't there” — and deployed where the business can act on them.
Summitview is a verified member. Microsoft independently confirmed our legal identity, business address and domain — you can check the listing yourself before you talk to us. Partner ID 7148376.
View our Microsoft profileThese aren't slides — we measured them in production. Read the engineering case →
What a data engagement leaves behind
Plenty of consultants hand you a pretty report and a dependency. We hand you a documented model your own team can extend after we're gone.
The data & BI stack we work in
How we work
We map the product, the user, the data you already hold, and the market reality. You leave week one with a scoped plan, not a vague estimate.
Data model, infrastructure, and security designed before a line of feature code. Compliance is planned, not bolted on.
Shipping in increments you can see and test. Real builds, real metrics, real costs — in the open, every week.
Launch, then the analytics loop that tells you whether it worked. We own results and iterate on evidence, not opinion.
Security & infrastructure
Your users trust you with their data. We architect every product so that trust is earned — from the first commit, not patched in after launch.
Why teams choose Summitview
We don't show mockups or NDAs you can't verify. We point you to the App Store, the Play Store, and live systems. The risk you usually take on a new vendor? We've already retired it.
Product, backend, infra, data and AI — no specialist handoffs, no finger-pointing.
We run our own products, so our analytics advice comes from operating them — not from a slide.
An American LLC with U.S.-compliant infrastructure — serving clients in the U.S. and Brazil alike.
Generative AI and ML are part of how we build and what we ship — embedded, not decorative.
You see builds, metrics, and costs in real time — never a quarterly surprise.
The engineering stack behind the work
Where we are
You contract a U.S. entity — American banking, American paperwork, American accountability. The work happens across teams that overlap your working day instead of replying tomorrow.
Summitview Land Holdings, LLC — incorporated in Florida. This is the entity you sign with, invoice, and pay in USD. All products are published under it on the App Store.
A working team on the ground, in Portuguese, in Brazilian business hours — with LicitaSmart as proof we build for this market, not just in it. Same U.S. contract, local conversation.
European operations, in progress. From 2027 our Portugal base serves EU and UK clients inside European hours and European contracting — the same team, closer to you.
Asia is where we go next, alongside Europe. Our Shenzhen base is scheduled for the third quarter of 2027. Until it opens, hardware, manufacturing and cross-border clients are served by our Brazil team — same U.S. contract, meetings in Chinese hours.
Straight answers
Usually yes. Most “Power BI is slow and nobody trusts it” problems come from the model, not the tool — flat imported tables, measures duplicated across reports, no clear grain. We audit first and tell you honestly whether it's worth repairing or rebuilding.
It depends entirely on how it's built, and most of what gets demoed is not reliable. What works in production is a pipeline, not a prompt: deterministic extraction first, embeddings for semantic matching, then a model acting as a judge that returns a score with a written justification — so a person can audit any single decision. Ours runs every day inside LicitaSmart, where it extracts 23–24 documents from a tender package that a commercial LLM read as 0–3, and turned a matching engine that produced zero useful hits out of 3,000 into dozens of real opportunities per week. If a vendor shows you a chatbot and no numbers, that's a demo.
We quote after we've seen the scope, never from a price list. Tell us what you're trying to do and we'll come back with a range and what drives it. Assessments are the cheapest way to find out whether the bigger project is even worth doing.
No. Every engagement ends with documentation, a handover session, and full ownership of the code and models on your side. Retainers exist because some clients want them, not because we engineered a hostage situation.
A fractional data team is an outside team doing the work of an in-house data department — modeling, pipelines, BI reports, machine learning — for a fraction of the cost of hiring an analyst, an engineer and a BI developer. You get the capability without the headcount, and you scale it up or down by the month. For most companies under a few hundred people, it's the only version of a data team that the budget actually supports.
Yes — Power BI with DAX and Power Query, SQL Server with SSIS, SSAS and SSRS, plus Azure SQL, Data Factory and Synapse. We also work in PostgreSQL, BigQuery and Python where those fit better, and we'll say so if they do.
Both, and often the same engagement. Plenty of clients come for a product and stay for the reporting layer — or arrive with a working system and no idea what it's telling them. We take data-only work with no app attached.
Summitview Land Holdings, LLC is a U.S. company — incorporated in Florida, and the entity you contract and pay. We have a local team in Brazil serving Portuguese-speaking clients in their own hours, a Portugal office opening in 2027 for European and U.K. clients, and a Shenzhen base opening in the third quarter of 2027 to serve China and Asia. Until that office opens, Asian clients are served by our Brazil team.
Send us the symptom — the report that takes four minutes, the refresh that dies on Sundays, the two numbers that never match, the pile of PDFs nobody reads. You get a straight answer, including “this doesn't need us”. You'll talk to the engineers who'd do the work, not a sales layer. We reply within one business day.
