How leaders of Brazilian mid-market companies are transforming data into revenue and operations at scale with the MyDatAgent Agent ecosystem.
How the BI Analyst Agent paired with the DataOps Agent increased product adoption by 35% and reduced CAC by 60%, transforming a reactive spreadsheet operation into an analytics intelligence ecosystem.
Sebrae managed a portfolio with dozens of products serving thousands of companies. Data operations were reactive: knowledge scattered across spreadsheets, manual analyses dragging on, and decisions guided by intuition.
Managers couldn't answer a simple question: "Which product should I recommend to this customer, right now?"
Data trapped in spreadsheets and legacy systems created information silos. Fragmentation caused inconsistency, security risks, and — worse — direct loss of opportunities.
Without analytics intelligence, CAC was high and adoption rates low. The data team spent time cleaning spreadsheets, not generating strategy.
We deployed the BI Analyst Agent paired with the DataOps Agent, with Medallion architecture (Bronze, Silver, Gold) to centralize data via Data Lake.
Automated pipeline in Airflow + DBT + Python, hybrid recommendation system (K-Means + collaborative filtering), and conversational BI agent running SQL on BigQuery — all with complete observability.
Decisions based on predictive data, advanced segmentation (from "Active Explorers" to "Churn Risk") and real-time recommendations in natural language.
Adoption +35%, CAC −60%, productivity +340%, executive alignment +42% — without growing the data team.
Centralized Data Lake with explicit layers for quality and governance. Each layer has contract and schema validation.
Extraction, cleaning, and standardization without human intervention. Zero manual CSV — scheduled and idempotent orchestration.
Algorithms cross NPS, engagement, and company stage to recommend the ideal product per customer — not the top seller.
Managers ask questions in natural language and get insights in real-time. SQL generated, executed, and audited with zero bias.
Spreadsheets, CRM, NPS, legacy systems — information silos without governance.
Cleaning, ETL, standardization and clustering (K-Means) — continuous, idempotent pipeline.
Conversational BI agent recommending the product with highest conversion probability.
The SDR Agent + Lead Scraper reduced CAC by 60%, tripled scheduled meetings, and made sales operations run 24/7 — without adding a single headcount.
Traditional B2B model required hiring more SDRs to scale. But 60% of their time was spent searching for leads on Google, cleaning company data, and sending generic WhatsApp messages.
Salespeople doing robot work; inconsistent pipeline; history lost on each SDR's personal phone.
Manual prospecting eats time and money. Unqualified leads clogging the pipeline, slow response times, stretched sales cycles.
Result: unsustainable CAC, zero predictability, and demoralized sales team doing what an AI agent could do in seconds.
We replaced manual effort with an orchestrated trio of agents — from raw data to meeting scheduled — natively integrated with HubSpot.
Lead Scraper enriches (45 fields in 35s), SDR AI qualifies via WhatsApp with Claude Sonnet, Outbound orchestrates cadences (D1, D3, D7, D14).
3× more scheduled meetings per month. 70%+ WhatsApp open rate (vs. 20% email). Payback in 60–90 days, projected ROI of 3× to 5× in year one.
Salespeople got back to what they do best: closing deals.
Collects and enriches leads in 35 seconds, crossing 45 fields (company ID, partners, validated WhatsApp) and applying quality Lead Score.
Makes first contact with a script personalized by pain point, qualifies interest, confirms ICP, and books the meeting — in natural conversation, not cold script.
Orchestrates follow-ups D1 · D3 · D7 · D14 with AI personalization, natively integrated with HubSpot. No generic cadence, no spam.
Conversation history, scoring, status and assignment to final human SDR — synced in real-time, no CSV or manual hacks.
Company ID on Google Maps, incomplete data.
Enriches 45 fields in 35s.
Qualifies via WhatsApp with Claude Sonnet.
Salesperson's calendar, ICP confirmed.
Synced, with complete history.
Our ecosystem is built on three pillars — all integrated, all governed, all Brazilian.
Specialized Small Language Models, trained with your company's data. More assertive answers, lower cost, no currency risk.
Your data in Brazilian private cloud, 100% LGPD compliant. Tier III+ certified datacenters, immutable audit logs.
From DataOps to MLOps with intelligent orchestration and AutoML for continuous deployment, A/B testing, and automatic rollback.
Before hiring tools, define the architecture. Our consulting assesses your data, selects the right agents, and ensures implementation drives real results.
Schedule a 30-minute strategic call with the AI team. You'll see the ecosystem running on a dedicated instance with your own use cases.