We torture data until it confesses.
Without data, you're just another person with an opinion, and in today's world, nobody has time for opinions. Give your data a voice.
Products built around how your business actually runs.
Every business says it wants to be data driven. Few ever get there, because most vendors sell you a single report and call the job finished. House of Analysis builds the full range: analytics products, data platforms, automations and AI systems, shaped around your industry instead of a template everyone else is already using.
| Department | Q1 | Q2 | Q3 | Q4 |
|---|---|---|---|---|
| Manufacturing | 142 | 158 | 164 | 171 |
| Stores & Purchase | 88 | 91 | 95 | 102 |
| Maintenance | 34 | 29 | 31 | 27 |
| Total | 264 | 278 | 290 | 300 |
Anomaly detected
Stores inventory variance exceeded threshold at 04:12.
Root cause drafted
Cross-referenced against PO log and maintenance schedule.
Summary sent
Notified stores lead via email, awaiting acknowledgement.
Power BI
- Faster to stand up
- Lower licensing cost
- Strong for departmental BI
Oracle Analytics
- Native Fusion / EBS integration
- Better for enterprise-wide rollout
- Deeper governance controls
One flagship report per industry.
These are sample previews built to show structure and style. Ask and we'll walk you through a full interactive version, or point you to a live published report.
Channel Analytics Dashboard
- ProblemBranch, ATM, mobile and call-centre data lived in five different systems with no shared view.
- ApproachOne semantic model unifying every channel, refreshed on the same schedule as the core.
- ShowsChannel performance, wallet share sizing, and SME portfolio, one screen. Click a bar to see its value.
Receivables Dashboard
- ProblemThe ageing report was a full day of manual Excel work every month-end.
- ApproachAutomated ageing buckets, DSO trending, and an editable writeback grid for Marketing.
- ShowsOverdue flags and DSO trend, with comments Senior Management sees the same day. Try typing above.
OEE: Overall Equipment Effectiveness
- ProblemNobody could say whether a stoppage was an availability, speed, or quality problem.
- ApproachOne OEE model, Availability × Performance × Quality, computed straight from shift logs.
- ShowsReal-time OEE against the 85% world-class benchmark, broken into its three components.
Wallet Share & Segmentation Dashboard
- Problem"Our best customers" was a gut feeling, not a number anyone could point to.
- ApproachA segmentation grid built on actual spend concentration, not assumptions.
- ShowsWhere spend concentrates. Hover any cell for that segment's wallet share.
Transaction Analytics Dashboard
- ProblemConversion and cart-abandonment numbers lived inside the payment gateway, unexamined.
- ApproachTransaction data piped straight from the app into a single analytics layer.
- ShowsConversion trend. Move your cursor along the line to read each point.
| Plan type | Usage | Churn | ARPU |
|---|---|---|---|
| Postpaid | 82% | 2.1% | $41 |
| Prepaid | 64% | 5.8% | $14 |
| Blended | 73% | 3.9% | $27 |
Usage & Churn Dashboard
- ProblemRetention found out a customer had churned only after the invoice bounced.
- ApproachUsage and ARPU trends modelled to flag risk before the renewal date.
- ShowsPlan usage, ARPU, and churn risk by segment, flagged before retention has to guess.
Real-Time Flight Tracking Dashboard
- ProblemLive position data and the compliance paperwork it feeds lived in separate systems.
- ApproachA live tracking feed wired directly into the same reporting cycle as compliance.
- ShowsLive position and status. Hover a blip for its flight code.
Operational KPI Dashboard
- ProblemEvery site reported output and load differently, nothing rolled up cleanly.
- ApproachOne standard KPI model applied consistently across every site.
- ShowsOutput, load, and efficiency at scale. Click a bar to see its value.
Three agents, doing actual work.
Not tech demos. This is what a chatbot, a voice agent, or an automation flow looks like when it's built to handle a real job, not just answer FAQs.
The Ops Chatbot
Lives in Slack or Teams. Answers "what were yesterday's numbers", flags anomalies before anyone asks, and hands off to a human the moment a question needs judgment, not data.
The Booking Agent
Picks up the call, speaks back in the caller's own language, finds a slot that works, books it, and sends a confirmation email before you've hung up.
"مرحبا، أريد حجز موعد قص شعر يوم الخميس"
"الخميس متاح، الساعة 4:30 أو 6:00 مساءً. أيهما يناسبك؟"
The Security Watch
Searches the web every morning for manufacturing-sector security news, summarises it into bullet points, and emails the digest. Each point links straight to the source.
Drag to see what "done" actually looks like.
Most businesses run on the left side of this slider without realising there's a right side available.
Paste your own numbers. Watch them become a chart.
This is roughly what the first hour of a real engagement looks like. Raw numbers turning into something you can actually read. Nothing you type here leaves your browser.
KPI Rush.
Spot the number that doesn't belong before your lives or the clock run out. Chain correct answers for a streak multiplier and climb this session's leaderboard. This is basically what anomaly detection feels like at 10x speed.
How much time is manual reporting actually costing you?
Drag the sliders to match your team's current routine. The estimate assumes roughly 70% of that time is automatable, which is conservative for most spreadsheet-based reporting.
Built by someone who has lived inside the problem, not studied it from outside.
House of Analysis was founded by a data professional who grew up in a small town with big ambitions and one habit that never changed: pick up a difficult problem and refuse to put it down until it makes sense. Seven years later, that habit is a full career inside enterprise data, serving clients across banking, manufacturing, finance, energy and aviation along the way. Data is not a buzzword here. It is the bread and butter.
Every product carries the same test: built somewhere that actually matters, on a live production floor, inside a real finance close, in front of an executive who wants an answer in one glance. Basic is the bare minimum, so it is not what we build here. We will not rebuild the dashboard template or the FAQ chatbot already sitting in a free tutorial online. What we build instead is specific to your business: a channel analytics product shaped around how a corporate bank really segments its customers, a stores product shaped around how your warehouse actually runs, an agent that watches for the one anomaly nobody has time to look for.
Call it craftsmanship, if that feels closer to the truth than software. House of Analysis is a young company built on a timeless standard of work, with a long runway ahead of it. The plan is simple: grow into a company that teams across the region trust by default, one product at a time.
Banking
Channel, wallet share & SME products.
Finance
Receivables, MIS & close reporting.
Manufacturing
Production, maintenance & stores.
Ecommerce
Transaction & conversion analytics.
Retail
Customer segmentation & footfall.
Communication
Usage, billing & churn tracking.
Aviation
Compliance reporting & live tracking.
Energy
Operational KPI tracking at scale.
A 360° approach. Zero noise.
Clients come back for the full picture: analytics, engineering, automation and AI, handled by one team that understands how all four connect. Data comes first here, always checked and trusted before a model or agent gets built on top of it. No inflated buzzwords, no chasing every new trend, just the shortest path from a real problem to an answer you can stand behind.
Data-first, not AI-first
The data and the pipeline get validated before AI ever enters the conversation. A chatbot or agent bolted onto bad numbers just repeats the mistake faster, so every AI or automation build here sits on a foundation that has already been checked, cleaned and trusted.
You own everything
Every product, model and script is yours outright at handover. No proprietary platform, no quiet lock-in you keep paying for.
Full-stack, not just the last mile
Database, pipeline, warehouse, product, automation or agent, built on Power BI, Microsoft Fabric, Oracle EBS, Azure and SQL Server. We work inside what your team already runs, end to end.
Cross-industry pattern matching
Patterns from banking, manufacturing and aviation show up in each other's products in ways most single-industry teams never get to see.
Privacy and security by default
Your data stays inside the systems you already trust and use daily. Access is scoped to only what a build needs, and nothing about your business leaves that environment without a clear, written agreement on where it goes.
Scoped before it's built
A blueprint gets reviewed before a single screen is built, so changes happen on paper, where they are cheap.
What clients will say. This space is reserved for their words, not ours.
House of Analysis is new enough that this section is still waiting on its first real quotes, and that says more about honesty than about the work. The layout is ready. Every placeholder below gets swapped for the real thing the moment it exists.
"[Client quote goes here, one or two sentences on the specific result they got, in their own words.]"
"[Another client quote, what changed for them, ideally with a number or timeframe.]"
"[Third client quote, what they'd tell someone considering the same project.]"
Four stages. Nothing built twice.
The plan gets reviewed before a single visual, screen, or workflow gets built, so changes happen on paper, where they are cheap.
Analyse
Understand the data, the decisions it feeds, and who's actually reading the report.
Draft
A blueprint of the model, metrics, and build plan, reviewed with you first.
Build
Short cycles, with something reviewable at the end of every one.
Handover
Docs and training, so your team can maintain it without calling us every time a filter breaks.
Signals, refreshed automatically.
A tech quote and the latest AI headlines, pulled live on every visit, so this page never looks quite the same twice.
Before you ask.
More than dashboards. The same engagement might include the database and pipeline behind it, an MIS pack for leadership, a chatbot or AI agent that acts on the data, or a Power Automate flow that removes the manual step entirely. We build whatever actually solves the problem, not just the part that's visible.
The name is new. The experience behind it isn't. Seven years of hands-on enterprise data work sit behind House of Analysis, so this is a new brand carrying work that's already been tested in production, not a first attempt.
Your data stays inside the systems you already use, we don't copy it into some separate platform of ours. Access is scoped to only what a build needs, and every engagement starts with a clear, written agreement on what data we touch and where it's allowed to go.
Most single-domain products land in 2 to 4 weeks from analysis to handover, built in short reviewable cycles rather than one long delivery.
Yes, most engagements start by auditing what's already there rather than rebuilding from zero.
Optional retainer support is available, but every build is documented and handed over so your team isn't dependent on it.
Bring us the problem.
We'll bring the blueprint.
Most projects start as a 20-minute call to figure out whether this is an analytics problem, a data problem, or something that needs a bot or an agent instead.