Unstructured to indicators
Read operational reports in any layout and turn them into a consistent, comparable set of KPIs.
Data intelligence platform
Your documents already hold the answers.
SmartDataLake ingests data from mailboxes, manual uploads, external connectors and multiple sources, relational or not. AI turns unstructured content, such as reports, PDFs, spreadsheets and emails, into governed, traceable indicators your whole team can trust.
From scattered files to trusted indicators
One path from raw data to decisions, with nothing to reformat first.
Collect
Data arrives from mailboxes, manual uploads, external connectors and multiple sources, relational or not. Nothing needs reformatting first.
Understand
Layout-aware readers and AI interpret each document and extract its tables, values and context.
Organize
Everything lands in a layered data lake: Raw, Silver and Gold, with quality checks between the layers.
Deliver
Each indicator is defined once, calculated once and served to dashboards, apps and APIs.
Everything around the data, in one platform
Beyond turning documents into numbers, SmartDataLake gives teams the tools to explore, question and govern them.
Prompt Builder
Design, test and reuse prompts that question your data. Link them to the files and tags that matter and keep a history of every answer.
Data views by domain
Explore data the way the business thinks about it: by domain, not by file. Every domain shows its latest state, its history and its gaps.
Data lineage
Trace any number back to the document and row it came from, and forward to every indicator that depends on it.
KPI catalog and builder
One governed catalog defines every indicator: name, formula, source and owner. Create new KPIs without rebuilding pipelines.
Automated Ingestion
From mailboxes, manual uploads and external data connectors to multiple sources, relational or not: ingestion happens automatically and the intelligent work starts the moment data arrives.
Data quality
Automated checks flag missing, duplicated or inconsistent data before it reaches a dashboard.
Open API
Serve indicators to any tool through a documented API, with the same definitions everywhere.
Access and audit
Role-based permissions decide who sees which data, and activity is logged.
Use case
Property management
A portfolio produces a steady stream of reports (occupancy, leasing activity, renewals, delinquency, maintenance), each in its own format and cadence.
SmartDataLake reads them as they arrive, standardizes the content per property and keeps the indicators current. Managers compare properties, follow trends week over week and click through to the exact report behind any figure.
- One consistent view across every property in the portfolio
- Daily and weekly indicators ready without manual compilation
- Every figure traceable to its source report, ready for owners and audits
Occupancy
Delinquency
Renewals
Maintenance
Cost-benefit and ROI
A faster return than a conventional data lake
A conventional data lake is a build project: connectors, custom parsers, pipelines, a catalog, lineage and quality tools, each assembled and maintained by a data team. SmartDataLake delivers those pieces already integrated, so the investment goes into answers instead of plumbing.
| Comparison | Conventional data lake | SmartDataLake |
|---|---|---|
| Time to first indicator | Long: design, connectors and pipelines come first | Short: connect a source and the indicators start to flow |
| Unstructured documents | A custom parser per report format, reworked whenever the layout changes | AI-assisted readers that adapt to layouts and extract tables and values |
| Data sources | One integration project per source | Mailboxes, manual uploads, connectors and relational or non-relational sources, ingested the same way |
| Tooling | Separate products for ingestion, catalog, lineage, quality and prompts | One platform with all of them built in |
| Who operates it | A specialized data engineering team | Business and data teams working in the same place |
| Trust and audit | Lineage and definitions documented by hand, if at all | Lineage and a governed KPI catalog generated as the data flows |
| When a source changes | The pipeline breaks and waits for a developer | Quality checks flag it and the readers adapt |
Faster time to value
Indicators start flowing as soon as the first source is connected, not after a long build.
Less manual work
Reports stop being compiled by hand, so people spend their time deciding instead of assembling spreadsheets.
Fewer tools to buy and maintain
Ingestion, catalog, lineage, quality and prompts come in one platform, with one contract and one team to run it.
Fewer errors and less rework
One definition per indicator and automatic quality checks remove the reconciliation loops between spreadsheets.
Estimate your return
Illustrative: replace the example values with your own.
Hours saved per month0
Estimated annual savings0
The estimate uses only the values you enter. Actual results depend on your sources and processes.