Custom business intelligence and reporting solutions that bring the data scattered across spreadsheets and systems into a single decision screen. Clean data through ETL, real-time KPI dashboards, and reports segmented by role.
Prepared by Pan Innovation House, a software company based in Gaziantep, Türkiye · Last reviewed:
Data, BI and reporting is the work of gathering the raw data accumulating in separate systems — production, sales, stock, accounting, the shop floor — into a single source of truth and turning it into dashboards a manager can read. The ETL data pipeline pulls data from the sources, cleans it and models it; the dashboards and KPI panels built on top show in real time how long which machine stood idle, what margin which product is making, or how far which dealer is from target. The aim is not to produce tables but to speed up decisions.
Most businesses still run these reports on hand-built Excel files. The files are copied afresh every month, formulas break, two departments give different numbers to the same question, and decisions are delayed. Off-the-shelf BI packages help up to a point, but they rarely capture your factory's actual calculation logic — your own shift definitions, your scrap and waste rules, or your dealer target formulas. That is exactly where custom development comes in: we build the dashboard around your metrics, your terminology and your approval flow.
We build on mature tools such as Looker and Metabase where appropriate, develop fully custom dashboards and API layers where needed, and often combine the two. The source code we write and your data are handed over to you as defined in the contract; third-party and open-source components remain subject to their own licences. The data model and documentation are handed over too. Because we work API-first, your dashboards can later connect to a new source, a mobile app or AI-assisted analysis. We take the few most critical metrics live first so you see the value early, then expand iteratively.
Production and quality managers at carpet, machinery, textile and food factories who want shift efficiency, machine downtime, OEE, scrap/waste rates and order fulfilment on a single dashboard. Shop-floor data flows straight into the panel, so you intervene without waiting for the end-of-day report.
Export and sales teams that want sales, profitability and collections across different currencies, countries and customer channels in one place. Market-segmented reports show clearly which country is growing in which product.
Business owners forced to rely on Excel and the scattered reports departments prepare. Those who want cash flow, stock turnover, open orders and cost items on a single executive dashboard, as one verified number.
Companies comparing sales targets, turnover and performance by dealer, branch or region. Those who need role-based, segmented reporting where each dealer sees only its own data and head office sees the whole network.
We build automated pipelines that regularly pull, clean, match and merge data from ERP, accounting, production and e-commerce sources. Repetitive manual copying ends; every morning the dashboard opens with current, consistent data.
We put the metrics that take your business's pulse — OEE, downtime, turnover, margin, open orders, collections — onto panels updated in real time or near-real time. Deviations from target show up instantly through colours and thresholds.
We design clean, fast-loading executive screens that support a decision at a glance. With filter-and-drill-down logic you can move from summary to line level, working with the right metrics rather than needless charts.
Different roles cut the same data differently: a dealer sees only its own figures, a regional manager their own region, head office everything. Permission-based visibility and masking of sensitive data are our standard approach.
We send daily, weekly or monthly reports automatically to the right people on a schedule, by email or as PDF/Excel output. We can trigger alerts when a threshold is crossed — for example when stock falls to a critical level.
We model scattered sources in a queryable, scalable data warehouse (PostgreSQL / BigQuery) and create a single source of truth. Metric definitions are held centrally; two departments no longer quote different numbers for the same metric.
On request we add a reporting assistant that answers natural-language questions, or layers that generate written commentary, producing summaries and interpretation with RAG and LLMs (Claude, OpenAI). We focus on measurable time savings, not on show.
Not every reporting need calls for a custom business intelligence project. The tables below set out four common routes, what the project covers and what it does not, and what you receive at handover.
The choice mostly depends on how many data sources there are, how specific your metric definitions are, how often dashboards must refresh, and how many people see the reports and with which permissions.
| Route | Enough when | Where it struggles | Cost structure |
|---|---|---|---|
| Spreadsheets and your ERP's standard reports | One source and a few metrics; a monthly or weekly report is enough. | Each report is prepared by hand, sources are not combined, and the same metric can come out differently for two people. | No licence cost; the hidden cost is preparation effort and inconsistent numbers. |
| A ready-made BI tool used by your own team (Power BI, Metabase, etc.) | Data sits in one or a few clean sources and someone on the team can use the tool. | If sources are scattered and messy, the tool alone does not fix them, and metric definitions drift from person to person. | Licence or subscription; some tools have an open-source edition. |
| A data pipeline and dashboards built on a ready-made BI tool | Most reports are standard; the real need is combining sources and creating a single source of truth. | Your own shift, scrap or profitability formulas may not fit the tool's templates fully. | Tool licence, plus a project fee for the pipeline and modelling. |
| A custom dashboard and data layer | Your metrics are specific to you and central to the dashboard; it must run inside another application or be opened to customers and dealers. | Development and maintenance take more effort; someone has to own the metric dictionary. | A project fee and a maintenance agreement. |
Scope is written down for every project during discovery. The split below shows the boundaries that most often get blurred in reporting projects.
| Area | In the project | Out of scope or agreed separately |
|---|---|---|
| Data pipeline | Secure connections to sources, extracting, cleaning and modelling the data; a metric dictionary. | Correcting faulty records in source systems is the job of the team that uses them; the pipeline makes errors visible. |
| Dashboards and distribution | Role-based dashboards and automatic report distribution. | BI tool licences and hosting costs are separate items. |
| Metric definitions and decisions | The calculation logic of each metric is defined with you and the numbers are validated with your sign-off. | Interpreting the numbers and making business decisions stay with management; a dashboard supports decisions, it does not make them. |
| AI-assisted analysis | If included in scope, asking questions in natural language or generating summaries. | The model provider's usage fees are a separate item, and generated commentary must be checked by a person. |
Handover covers the dashboards and the pieces that explain where the numbers come from and keep the system alive.
| Deliverable | What it is for |
|---|---|
| Data pipeline and data model | Sources are pulled regularly and combined in one place. |
| Metric dictionary | The calculation logic of each metric is written down, so the same number shows on everyone's screen. |
| Dashboards and automatic reports | Everyone sees the dashboard for their role, and periodic reports are no longer prepared by hand. |
| Monitoring | Pipeline errors and unexpected changes in a source are noticed. |
| Source code | The source code we write and your data are handed over to you as defined in the contract; third-party and open-source components remain subject to their own licences. |
If these are ready, the first call is concrete; we can fill any gaps together during discovery. The first 30-minute call is free; the scope of an on-site discovery, and its fee if any, is agreed in writing during that call.
We discuss which decision you want to speed up, and pin down together the KPIs to track and the exact calculation logic of each (shifts, waste, target formulas). We review your data sources and their quality.
We connect securely to the sources, pull the data with ETL, clean it and model it in the data warehouse. We fix metric definitions in a central dictionary and establish the single source of truth.
We quickly take live a first dashboard covering the few most critical metrics. You see the value early, on a real screen with real data, and we confirm the accuracy of the numbers with your sign-off.
With your feedback we add new dashboards, segments, drill-downs and automated distribution. Every release goes through a review step and number validation before it goes live.
We monitor the pipelines, catch data drift and errors, and keep the dashboards current as sources change. With monthly maintenance, defined in the contract, the system keeps producing value for as long as it lives.
For standard reports, ready-made tools such as Metabase are fast and suitable, and in most projects we build on them ourselves. But if your own shift, waste, target or profitability formulas are the heart of the dashboard and no ready-made template captures them fully, custom modelling and a custom dashboard layer are more accurate and more flexible in the long run. In discovery we compare both options.
Timeline and cost depend mainly on the number of data sources to connect, how clean the source data is, how far the metric definitions are agreed, refresh frequency, and the number of dashboards and users. A first executive dashboard can take a few weeks; a multi-source data warehouse with broad reporting can take a few months. Because we work iteratively, the cost firms up after discovery; we do not invent figures — it grows with the scope. We take the most critical metrics (an MVP) live first so you see the value early.
The source code we write and your data are handed over to you as defined in the contract; third-party and open-source components remain subject to their own licences. The data warehouse, ETL pipelines, dashboard code and documentation are part of that handover. Your data sits on your own infrastructure or the cloud you choose; you can carry on with another team whenever you wish.
Yes. Reading data from systems such as Logo and SAP, and from databases, is usually possible; the route depends on the version and the access you are given, and is established during discovery. We stream e-invoice data via your integrator, and PLC/SCADA and barcode data from the production line, into the dashboard. Combining multiple sources in a single model is this module's core job.
It is tuned to the need. For some metrics we build near-real-time flows (within minutes); for some reports an hourly or nightly batch refresh is sufficient and more economical. We decide together how often each metric needs to update.
Yes. We offer monthly maintenance packages, with scope and response times defined in the contract, covering monitoring of the ETL pipelines, catching data inconsistencies, updating dashboards as sources change, and new report requests. A BI system earns trust not at go-live but by staying continuously current.
A dashboard is an interface that shows a business's key metrics on a single screen with charts, summary cards and tables, so the state of the data can be read at a glance. A good dashboard is designed not to produce tables but to speed up decisions: it shows straight away how long a machine has been down, or where a dealer stands against target. We build dashboards around your metrics, your terminology and your roles, and take them live first with the few most critical metrics.
Business intelligence (BI) is the set of methods and tools that collects and cleans raw data from different systems, models it in a single source of truth and turns it into the reports and dashboards that support decisions. At its core are an ETL data pipeline, a data warehouse and a visualisation layer. We build on mature tools such as Metabase and Looker where that fits, and develop fully custom dashboards and API layers where it does not.
We listen to what you need and tell you whether custom development or an off-the-shelf product fits better. The first 30-minute call is free; the scope of an on-site discovery, and its fee if any, is agreed in writing during that call.
We develop custom automation solutions that remove repetitive manual work, copy-paste reporting and waiting on approvals — and connect your systems to each other.
Details →This is not an off-the-shelf chatbot but an AI layer that works on your own data and produces measurable gains. We weave chatbots, customer assistants, document understanding (RAG), internal search and report generation into your organisation's processes — and the source code we write is handed over to you.
Details →We go beyond an assistant that answers questions and build workflows that complete work in multiple steps: classifying the incoming request, pulling data from your systems, checking the rules, opening the record and dropping to human approval where needed. Every step has defined permissions; every step leaves a recorded trail.
Details →We build a layer that reads incoming invoices, delivery notes, specifications and customs documents field by field and posts them into your ERP. It validates every field it reads against your own records, routes anything it is unsure of for approval, and keeps a record of which value came from which part of which document.
Details →We develop solutions built on Turkish speech recognition and synthesis: call recordings transcribed and made searchable, topic and sentiment analysis, a voice assistant on the order line, and voice-driven data entry for field staff whose hands are full.
Details →For organisations that will not let their data leave the building, we build model infrastructure that runs on your own servers or in your own cloud tenancy: hardware planning, model selection, internal document search, routing that decides which job goes to which model, and cost measurement.
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