Automated data validation for a supermarket loyalty platform
- ~99%
- automated validation accuracy, up from ~80%
Automated Reporting Software
Every report that requires someone to manually pull data, format a spreadsheet, and email a PDF is work that happens again next week, and the week after.
Automated reporting replaces manual report production with scheduled, system-generated reports that run without human involvement. The data pulls, the calculations run, the report formats, and the output goes to the right recipients on the configured schedule, whether that's a daily operational report to department managers, a weekly sales report to the leadership team, or a monthly client report to 200 customers. RaftLabs builds automated reporting software for internal management reporting and external client reporting. Data extraction, calculation, report generation in the required format (PDF, Excel, web view), and delivery to configured recipients. Every report includes data validation before generation, so the report either contains correct data or doesn't generate, rather than distributing numbers that are wrong.
Scheduled report generation running without human involvement, daily, weekly, monthly, or triggered by a business event
Data validation before each report run, wrong data triggers an alert rather than a report with incorrect numbers
Report delivery via email, Slack, or secure client portal, configurable per report and per recipient
Parameterised reports where each recipient automatically receives a report scoped to their data (their accounts, their region, their department)
Recent outcomes
Voice AI · Research
6× deeper insights
Text-based interviews converted to automated phone calls
AI Automation · Ops
20k+ txns day one
Manual invoice OCR across 40+ gas stations
Loyalty · Retail
1,062 users in 4 weeks
SuperValu & Centra loyalty platform with receipt validation
SaaS · Logistics
2,000+ shipments yr 1
Multi-carrier shipping hub for Indonesian eCommerce
4.9
on ClutchThe problem
Sound familiar?
How many analyst or operations hours per week go into manually assembling reports that could be generated automatically from the same data, and what would those people do with that time instead?
When a manually assembled report contains an error that reaches a client or the board, how long does it take to identify the mistake and what is the cost of the correction?
Short answer
RaftLabs builds automated reporting software that replaces manual report assembly with scheduled data extraction, validation, generation, and delivery via email, Slack, or a client portal. A first report automation starts around $8,000 to $20,000 and goes live in 6 to 10 weeks. It grows into a full parameterised reporting platform with client reporting and a delivery portal, around $25,000 to $70,000, at a fixed cost agreed upfront.
Key takeaways
- Automated report generation runs on a schedule or business event trigger without human involvement, covering daily, weekly, and monthly cadences
- Data validation runs before every report generation cycle and blocks delivery if any check fails, preventing wrong numbers from reaching recipients
- A first report automation starts around $8,000 to $20,000 and goes live in 6 to 10 weeks, the v1 slice you validate before expanding
- That first automation grows into a full reporting platform with parameterised client reporting and a delivery portal, around $25,000 to $70,000, all at a fixed price agreed before work starts
- Parameterised report templates generate individualised reports for every client from a single template, with each recipient receiving only their own data via email, Slack, or a secure client portal
Trusted by
Manual report assembly carries a cost that rarely shows up on any budget line. Picture the analyst who exports data from three systems each Friday, pastes it into a spreadsheet, formats it, runs the calculations, notices one number looks off, tracks down the source, fixes it, and emails the final version to 15 people. That takes hours, and it repeats every week. Multiply it across every recurring report the business produces and the total is large, none of it creating any analytical value.
The cost of error is harder to quantify and often bigger. A manually assembled report reaches a client or the board carrying a bad figure: a formula broke, a filter still pointed at last month's template, or a copy-paste landed in the wrong cell. Now the mistake has to be found, corrected, and explained. The decisions already made on that number before anyone catches it add to the bill. Validation before generation does not make bad numbers impossible, but it changes the failure mode: the report fails to build and an alert fires, rather than a wrong figure going out to 20 people.
The waste is well documented. For teams running recurring reports the ratio skews higher still, the same data pull, the same template, the same email, week after week.
The cost of doing it by hand
- of workers lose at least a quarter of the week to manual, repetitive tasks
- 40%+
- Smartsheet, Automation in the Workplace
- average yearly cost of poor data quality per organisation
- $12.9M
- Gartner
Capabilities
What we build
- 01Report template development
Report templates defined per report type, with layout, sections, charts, and data field mappings specified before any extraction logic is written. A single parameterised template generates reports for every recipient: the account manager sees their accounts, the regional director their region, the CEO consolidated totals. The first run produces a sample report the data owner signs off before automation goes live.
- Built with
- Git
- 02Data extraction and calculation
Scheduled data extraction from source systems, with extraction logic documented as versioned code rather than a manual query someone has to remember. Metric calculations are version-controlled, so a definition change never silently alters historical reports. For board packs and compliance reports, every figure carries a lineage record tracing it back to its source data and calculation.
- Built with
- PostgreSQL · Snowflake · Salesforce · HubSpot · Stripe · dbt or Python
- 03Data validation before generation
Data validation is the step that converts automated reporting from a convenience into a trustworthy system. Checks run before every generation cycle and block delivery if any fail: completeness, freshness, value ranges, and referential integrity. Metrics that deviate sharply from the trailing 8-week trend are flagged for human review, so commercially implausible numbers never reach recipients.
- Built with
- Great Expectations · Slack alerts
- 04PDF and Excel report generation
Report output format selected by use case: PDF for client-facing reports, board packs, and compliance reports where layout must stay locked, and Excel for operational reports teams need to sort, filter, and pivot. Charts embed as vector graphics so nothing pixelates in print, and client-facing reports carry your branding with white-label templates per client tier.
- Built with
- Puppeteer
- 05Parameterised client reporting
Per-client reporting is where the automation earns its keep: a single template produces individualised reports for every client on your roster, each containing only their own data. Adding a new client is a configuration record, not a code change. A client portal gives each client secure access to current and historical reports, and the account team can trigger ad-hoc runs and manage recipients without engineering involvement.
- 06Delivery and scheduling infrastructure
Scheduling and delivery infrastructure ensures reports arrive on time, to the right recipients, without silent failures. Runs trigger on a schedule or a business event such as month-end close, and wait for upstream ETL to finish before starting. Every delivery is logged, transient failures retry automatically, and if a scheduled run misses its heartbeat an alert fires to the team within 20 minutes.
- Built with
- Cron · SendGrid or AWS SES
Before you automate
Reporting-readiness checklist
- 01Pin down the single source of truthDecide which system owns each number before anything gets automated. If sales sits in the CRM and revenue in the finance ledger, the report has to know which one wins when they disagree. Automation settles that every run, so settle it once, on purpose.
- 02Write the metric definitions downA metric everyone "knows" is a metric nobody has defined. Fix what counts as an active customer, a closed deal, or recognised revenue in version-controlled logic, so a definition change never silently rewrites last quarter's numbers.
- 03Name the cadence and the triggerSome reports run on the clock: daily, weekly, month-end. Others should fire on a business event, like a close completing or an upstream data load finishing. State the schedule and the upstream dependency for each report before anyone builds it.
- 04Set the data-freshness and delivery SLAAgree how current the data must be and when each report is due. A board pack that must reflect a completed close is a different job from an operational report that tolerates data an hour old. The SLA decides what the pipeline waits for before it starts.
- 05Decide what happens when a check failsAgree up front that a report with missing or implausible data does not go out. A partial report is often more dangerous than none, because recipients rarely notice a section is missing. Route the failure alert to a named owner, not a shared inbox.
- 06List the recipients and the format per reportPDF for locked client-facing and board layouts, Excel for operational reports teams sort and pivot. Write down who receives each report, in which format, on which day, so the template and the schedule scope to real people rather than a guess.
Have a reporting automation project?
Tell us which manual reports take the most time to produce, who receives them, and how often they go out. We'll scope the automation and give you a fixed cost.
Related business intelligence services
Business Intelligence and Analytics, full BI capability overview
Executive Dashboard Development, executive dashboards complementing automated reports
KPI Reporting System, structured KPI reporting with period comparison
Self-Service Analytics Platform, ad-hoc analytics alongside scheduled automated reports
What clients say
What our clients say
Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.
Charles E.
USAEntrepreneur at Aggie Technologies
All of the sprints were completed on schedule and on budget. We highly recommend RaftLabs!
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Read moreFrequently asked questions
A BI dashboard is an interactive tool users log into to explore data, they choose filters, change date ranges, and navigate between views. Automated reporting generates a fixed, formatted output (PDF, Excel, or web view) on a schedule and pushes it to recipients who don't need to log in or interact with the data. Both have a role: dashboards for active monitoring and exploration, automated reports for structured delivery to recipients who need a formatted summary without interacting with a live system. Most organisations use both, connected to the same data layer.
Yes. Parameterised report templates pull the client identifier from a configuration and scope all data extractions and calculations to that client's records. A single report template generates 200 client-specific reports without manual intervention, each containing only that client's data. Client report delivery is configured per client: email address, delivery day, preferred format. New clients are added to the report schedule by adding a configuration record, not by writing new report code.
Report generation failures are handled transactionally: if any step in the generation pipeline fails, data extraction, validation, report rendering, the report is not delivered and the failure is logged and alerted. Partial reports, where some data extracted correctly and some failed, are not delivered because a partial report is often more dangerous than no report. Recipients may not notice that sections are missing. The failure alert goes to the report owner with the specific failure step and error details for investigation before the next scheduled run.
Automating your first manual report, one specific data assembly and formatting process, starts around $8,000 to $20,000 and goes live in 6 to 10 weeks. That first automation is the slice you validate before expanding. It then grows into a full reporting platform covering multiple report types, parameterised client reporting, a client portal, and delivery infrastructure, around $25,000 to $70,000. Fixed cost is agreed before work starts, so there are no surprises at the end.
Work with us
Tell us what you need. We'll tell you what it would take.
We scope Automated Reporting Software in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.
- Scope and cost agreed before work starts. No surprises. No obligation.
- Working prototype within 3 weeks of kickoff.
- Pay by milestone. You see progress before each invoice.
- 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
- All conversations are NDA-protected.