Ortem Technologies

    Turn Reported Numbers Into Decisions

    Data Analytics & BI — Business Intelligence & Data Analytics Services

    Business Intelligence, Dashboards & Self-Serve Analytics

    Dashboards your executives actually open, metrics everyone agrees on, and self-serve analytics that stop every question becoming a ticket for the engineering team.

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    Clients Worldwide
    300+
    Projects Delivered
    1,000+
    Rated on Clutch & GoodFirms
    5/5
    Years Experience
    13+

    Quick Answer

    Dashboards your executives actually open, metrics everyone agrees on, and self-serve analytics that stop every question becoming a ticket for the engineering team.

    At a glance

    Overview

    Most companies do not have a data problem — they have a decision problem. The numbers exist, but they live in six systems, three spreadsheets and one analyst's head, and by the time anyone assembles them the moment has passed.

    We build the layer that sits above your data infrastructure: agreed metric definitions, dashboards that answer real operating questions, and reporting your team trusts enough to act on without re-checking it in Excel.

    That is deliberately a different job from moving and storing the data. If your pipelines are unreliable or your warehouse is not modelled yet, start with data engineering — analytics built on a shaky foundation just produces confident wrong answers faster. If what you actually need is a model that predicts something rather than a report that explains it, that is AI & ML.

    Our services

    What We Build

    Executive & Operational Dashboards

    Reporting built for a specific audience and decision cadence — board packs, weekly operating reviews, or live floor dashboards.

    • KPI and metric tree design
    • Role-based views and access
    • Drill-down from summary to detail
    • Scheduled and alert-driven delivery

    Metric Definition & Governance

    A single documented source of truth for how each business metric is calculated, so finance, sales and ops stop reconciling different numbers.

    • Metric catalogue and documentation
    • Semantic layer modelling
    • Definition change control
    • Cross-team sign-off workshops

    Self-Serve Analytics Enablement

    Curated datasets and guardrails that let non-technical teams answer their own questions without filing a request or writing SQL.

    • Curated, business-ready datasets
    • Guided exploration templates
    • Team training and enablement
    • Usage monitoring and iteration

    Embedded Product Analytics

    Customer-facing reporting inside your own application — the dashboards your users log in to see, built to your design system.

    • In-app dashboards and charts
    • Multi-tenant data isolation
    • Export and scheduled reports
    • Performance tuning for large accounts

    Analytics Audit & Rescue

    A fixed-scope review of reporting you already have: what is wrong, what is unused, what is contradicting itself, and what to fix first.

    • Dashboard inventory and usage review
    • Metric discrepancy investigation
    • Prioritised remediation plan
    • Tooling and cost assessment

    Why Ortem

    Why Run Your Analytics Work With Ortem?

    One Agreed Definition Per Metric

    Most reporting disputes are definition disputes. We pin down what "active customer" or "gross margin" means once, document it, and make every dashboard read from that single definition.

    Dashboards Built Around Decisions

    We start from the decision a dashboard is meant to support, not the fields available in the database. Anything that does not change what someone does gets cut.

    We Will Tell You If You Need Engineering First

    Analytics on unreliable data is worse than no analytics. If the real blocker is upstream, we say so and scope the foundation work instead of shipping dashboards over broken inputs.

    Your Team Keeps Working Without Us

    Documented models, a semantic layer your analysts can extend, and training on handover. The goal is that you stop needing us for routine questions.

    Before / after

    What changes when it's done right

    Where teams struggle

    • Every Report Says Something Different

      Finance, sales and ops each have their own version of the same number, and meetings start with reconciling them.

    • Dashboards Nobody Opens

      Reporting was built once, never matched how the team actually works, and quietly got replaced by spreadsheets.

    • Every Question Is An Engineering Ticket

      Simple business questions queue behind the roadmap because only two people can write the query.

    The Ortem advantage

    • One Source Of Truth

      A documented definition per metric that every dashboard reads from.

    • Decisions Without Delay

      Answers available when the decision is being made, not a week later.

    • Analyst Time Back

      Self-serve access removes the routine request queue from your technical team.

    • Reporting You Can Defend

      Every headline number reconciles to a trusted source before it ships.

    Our process

    How does our process work?

    1. 01

      Decision Mapping

      We interview the people who will use the reporting and work backwards from the decisions they need to make each week.

    2. 02

      Metric Definition

      Agree and document the calculation for every metric in scope, and surface where existing reports currently disagree.

    3. 03

      Model & Build

      Build the semantic layer and dashboards, reviewed with real users at the halfway point rather than at the end.

    4. 04

      Validate Against Reality

      Reconcile every headline number against a trusted source before launch. Nothing ships that cannot be tied out.

    5. 05

      Handover & Enablement

      Training, documentation, and a defined path for your team to extend the models without us.

    Industries we serve

    Which industries use data analytics & bi?

    Proven results

    Success Stories

    View all case studies →
    Web & Mobile Ecosystem Enhancement for System Loco

    Transportation & Logistics

    Web & Mobile Ecosystem Enhancement for System Loco

    Transformed complex IoT data into an elegant, user-friendly interface that scales effortlessly across global operations while integrating real-time tracking devices, predictive analytics, and supply chain visibility tools into one cohesive platform.

    Significant Improvement
    Customer Engagement
    Above Expectations
    Platform Performance
    Read case study
    Residenta — AI-Powered Property Management SaaS

    Real Estate & PropTech

    Residenta — AI-Powered Property Management SaaS

    Built Residenta — a full-stack AI-powered property management SaaS that replaces fragmented spreadsheets and email-based workflows with centralised lease management, AI maintenance ticket classification, predictive maintenance forecasting, financial tracking, a resident self-service portal, and real-time notifications. Designed to scale from 10 units to 10,000 with the same team size.

    60% faster
    Maintenance Resolution
    94%+ on-time
    Rent Collection Rate
    Read case study
    CommercePulse — Unified Data Warehouse & Real-Time Revenue Intelligence

    E-commerce

    CommercePulse — Unified Data Warehouse & Real-Time Revenue Intelligence

    A cloud-native data platform for a multi-brand retailer operating across Shopify, Amazon, paid media, HubSpot CRM, NetSuite ERP, and a third-party fulfilment provider. CommercePulse consolidates fragmented commercial data into a governed Snowflake warehouse, powers near-real-time revenue and inventory reporting, and gives finance, operations, and marketing one trusted definition of performance.

    82% faster — multi-day reconciliation reduced to same-day reporting
    Reporting Turnaround
    Under 12 minutes for sales and inventory metrics
    Priority Data Freshness
    Read case study

    Delivery Markets

    Where companies buy Data Analytics & BI

    These market pages reinforce geographic relevance and connect this service pillar to regional buying-intent pages with stronger local context.

    Data Analytics & BI for United States

    See how Ortem positions data analytics & bi for United States buyers, including market fit, delivery overlap, and local decision context.

    View market page

    Data Analytics & BI for United Kingdom

    See how Ortem positions data analytics & bi for United Kingdom buyers, including market fit, delivery overlap, and local decision context.

    View market page

    Data Analytics & BI for United Arab Emirates

    See how Ortem positions data analytics & bi for United Arab Emirates buyers, including market fit, delivery overlap, and local decision context.

    View market page

    Get a Free Analytics Review

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    About Ortem Technologies

    Ortem Technologies is a premier custom software, mobile app, and AI development company. We serve enterprise and startup clients across the USA, UK, Australia, Canada, and the Middle East. Our cross-industry expertise spans fintech, healthcare, and logistics, enabling us to deliver scalable, secure, and innovative digital solutions worldwide.

    FAQ

    Frequently Asked Questions

    It depends on where the pain is. If your reports disagree with each other, nobody trusts the numbers, or leadership cannot get a straight answer — that is an analytics problem and this is the right starting point. If your analysts spend most of their time cleaning data, pipelines break silently, or dashboards go stale because loads fail, the blocker is upstream and you want data engineering first. We will tell you honestly which one you are looking at during the review.

    Analytics explains what happened and why; machine learning predicts what will happen next. Dashboards, KPI reporting and self-serve exploration sit here. Demand forecasting, churn prediction and anomaly detection sit with AI & ML solutions. Plenty of clients need both, and they are usually sequenced — reliable reporting first, models second.

    Yes. We work with whatever you have already bought and trained people on rather than pushing a migration you did not ask for. If your current tool genuinely cannot do what you need, we will say so and show the tradeoff, but replacing it is a last resort, not an opening move.

    A fixed-scope analytics audit is the usual entry point and is priced as a standalone piece of work. Full dashboard and semantic-layer builds are scoped after that, because cost depends almost entirely on how many source systems are involved and how much disagreement there is between existing definitions. You get a fixed quote before any build starts.

    Almost always because the same metric is defined differently in each one — a different date field, a different exclusion rule, a different treatment of refunds or cancellations. This is the single most common problem we are called in for. The fix is a documented definition per metric and a semantic layer that every report reads from, rather than each dashboard re-implementing the logic.

    Yes — embedded, customer-facing analytics is a distinct offering here. It carries requirements internal reporting does not: strict multi-tenant data isolation, your design system rather than a vendor look, and query performance that holds up for your largest accounts. We build it as part of the product rather than bolting on a third-party iframe.