BlueliftAI

Business Intelligence · Paraguay

Business Intelligence for companies in Paraguay: where to start

Start with the sales and collections report management asks for every month: a dashboard that updates itself, with every figure defined. AI drafts the summary; what each number means and what gets decided stays with your management.

Start now if

  • Every meeting starts by arguing which number is right
  • Someone loses days building the monthly report
  • Sales and collections are already recorded in a system

Not yet, if

  • There is no agreement on what to measure
  • Sales are written down in notebooks
Are you ready? 30 seconds ↓

Real process · example timings

Monthly sales and collections report for management

Today

  1. 1Pull sales from the ERP and collections from the treasury spreadsheet30 min
  2. 2Paste into Excel and fix miscoded branches and salespeople1 h 30 min
  3. 3Argue with each area about which figure is right+1 day
  4. 4Build charts and email the report2 h

With AI

  1. 1Sales and collections refresh on the dashboard every dayauto
  2. 2Checks warn when a figure drifts from what is expectedauto
  3. 3AI drafts the monthly summary and the owner reviews it20 min
  4. 4Management opens the dashboard in the meeting10 min
Today≈ 4 h of work + 1 day waiting
With AI≈ 30 min
Illustrative timings, not client measurements.

Ready for a pilot?

Tick what you already have; heavier items stall a pilot more. Nothing is sent.

Readiness for a management dashboard

0 % · 0 of 6 controls that applyFirst missing: report measured and metrics defined

Not yet: the basics for showing reliable numbers are missing.

Higher-risk controls weigh more in the score.

What it costs and when it pays back

Hours freed by AI minus what it costs to run. Examples are marked; public prices link to their source.

60
4 h
0.5 h
5
AI model
Floor: the minimum-wage hourly value (MTESS, July 2026). Typical real cost (example): ×2.5, a salary of two minimum wages plus employer contributions and the 13th month. Source
Today240 h/month
Automated30 h/month
Value of hours freed per month210 h × PYG 12,683
PYG 2,663,430
AI model public price60 reports × USD 0.0013 (example: 8,000 input + 1,000 output tokens; gpt-6-luna at USD 0.10 / 0.50 per million) · OpenAI · API pricing
−PYG 444
BI licences per user public price5 users × USD 14 to 24 per month (Power BI Pro or Premium Per User, billed yearly) · Microsoft · Power BI pricing
−PYG 398,613 to −PYG 683,336
Platform, monitoring and support exampleTypical monthly range
−PYG 455,558 to −PYG 1,138,894
Net savings per month
PYG 840,755 to PYG 1,808,815
Indicator definitions, ERP connection, checks and first dashboard typical range · exampleOne-off, up front
PYG 11,388,940 to PYG 28,472,350
Months to pay back the investment
6.3 to 34 months

Tokens: the unit AI providers bill for the text the model reads (input) and writes (output). OpenAI puts 100 tokens at about 75 English words.

Range: the lower figure uses low costs, the higher one high costs. Public prices checked on 11 Oct 2026. USD prices converted at PYG 5,694.47 per dollar (reference rate of 9 Oct 2026): BCP

estimated

4-week pilot

A typical plan; real timing depends on your systems.

Pilot · weeks 1 to 4

  1. Week 1Pick and measureOne report (sales and collections) and the hours it takes today.KPI: Signed baseline
  2. Week 2Define indicatorsManagement agrees what each figure means and which system it comes from.KPI: Definitions approved
  3. Week 3Dashboard and checksDashboard with daily refresh and alerts when a figure does not match.KPI: Figures that match the ERP
  4. Week 4Real useManagement uses the dashboard in its meetings and it is compared to the baseline.KPI: Hours per report vs. baseline

Before you start

Frequently asked questions

What dashboard tool do you use?

Whichever best fits your case and budget: Power BI, Looker Studio, Metabase or another. The tool is interchangeable; the reliable data foundation is what we build to stay.

We have dashboards but nobody trusts the numbers. What do we do?

That's the most common case we handle. We audit where each number comes from, fix the pipelines and document the definitions. The dashboard can almost always be kept.

How long until the first reliable dashboard?

A first set of KPIs on scoped sources is usually in production within 3 to 5 weeks, including metric definition with your team.

Can we move on to AI and forecasting after BI?

Yes, and it's the right path: with unified, reliable data, adding forecasts or AI agents is a natural step and far cheaper than starting with AI.