Top 10 AI Tools Every Finance Professional in Brazil Should Know in 2025

Brazil's finance teams face a turning point in 2025: tightening rules such as Public Consultation 117/2025 have even Nubank weighing a bank acquisition to secure full-license capabilities, raising the bar for compliance, scale and customer trust - and with more than 100 million customers at stake, automation isn't optional (Nubank regulatory context and market moves (Public Consultation 117/2025)).

AI tools that automate forecasting, anomaly detection, cash-forecasting and on‑brand reporting let analysts trade busywork for insight; industry roundups like AI finance tools roundup 2025 - top AI-driven finance tools for FP&A and spend control map options for FP&A, close automation and spend control.

Practical skills matter as much as platforms, so finance pros in Brazil should pair tool pilots with training - Nucamp's AI Essentials for Work bootcamp (prompt-writing and workplace AI skills) teaches prompt-writing and workplace AI use to turn hours of formatting and reconciliation into decision-ready minutes.

These are just a few examples of the many ways AI is being used today.

Selection began with Brazil-specific guardrails: every candidate had to demonstrate paths to LGPD compliance, support for DPIAs and human‑in‑the‑loop controls aligned with the risk‑based approach in Bill No.

2,338/2023, and clear data‑provenance or contractual assurances to manage TDM and IP risks (legal and regulatory context summarized here: Brazil AI law and Bill No. 2,338/2023 - trends and developments).

Tools were then scored for finance fit (AML/transaction monitoring, credit‑scoring explainability and close automation), Portuguese language/local deployment options, vendor transparency (audit logs, model cards, vendor warranties) and commercial practicality - ease of piloting, training needs and procurement clauses that reflect Brazil's procurement risks.

Priority went to solutions built for regulated environments (financial‑grade security and contractual indemnities), those that simplified governance (automatic event recording, impact assessments) and offerings that reduced manual reconciliation without adding opaque automation.

Final weighting also reflected scale and sustainability: Brazil's PBIA commitment (BRL23 billion 2024–28) and rising central‑bank standards push preference toward vendors who can demonstrate enterprise governance and low operational carbon intensity.

The result: a short list of tools that balance compliance, explainability and real‑world finance productivity so teams can pilot quickly and govern confidently.

“The job of central banks as stewards of the economy will be directly affected as frontline users of AI tools,”

For Brazil's finance teams, the Bloomberg Terminal remains the short‑list, enterprise‑grade workbench for real‑time market data, execution and deep analytics - a single pane that brings news, FX and bond desks, and portfolio tools together with the trademark black interface that feels like a trading cockpit; the platform's value is in turning streams of ticks and macro updates into actionable signals for monitoring central‑bank moves, currency shifts and sovereign‑debt spreads relevant to Brazilian issuers (see a concise Bloomberg Terminal overview for finance professionals).

Its integrated trading and charting toolset and mobile/Bloomberg Anywhere access make it practical for dealers and corporate treasuries, while the detailed function library (FX matrices, yield‑curve tools and fixed‑income pricing) is documented in guides to the TrendSpider guide to Bloomberg real-time data and trading tools and a library guide to Bloomberg FX and fixed‑income functions.

The premium comes with a premium price - expect institutional subscription costs - so pilot plans should aim to capture specific Brazil‑focused workflows (FX hedging, sovereign surveillance, and regulatory reporting) that justify the cost.

For Brazil's finance teams needing fast, auditable intelligence, AlphaSense combines analyst‑grade search with secure enterprise controls to make research feel like a trading‑room superpower: one click can turn a single ticker into a full‑scale research engine and AlphaSense's Deep Research can compress weeks of diligence into minutes, surfacing citable insights and Smart Summaries that speed earnings prep, M&A diligence and competitive benchmarking (see the AlphaSense generative search platform and Deep Research for details: AlphaSense platform - generative search & Deep Research).

Enterprise Intelligence lets firms index internal memos, CIMs and slide decks alongside 10,000+ premium sources and snaps into SharePoint, Box and Google Drive with permissioning and the assurance that client documents aren't used to train vendor LLMs - features that make it practical for regulated Brazilian teams to centralize knowledge while keeping audit trails intact (AlphaSense Enterprise Intelligence integrations & security).

“It's super helpful that I can actually upload docs, and search through all of our library. Sometimes it takes a while to get up to speed on an industry. This speeds up that process a lot.”

Fiscal.ai (formerly FinChat.io) is a low-cost, conversational research terminal that pairs institutional-grade global financial data with an AI “Copilot” to shave hours off earnings‑call reviews and dense filings - useful for Brazil's time-pressed analysts and SMB treasuries who need fast, citable answers without a full terminal bill; the platform offers a free tier plus paid plans, SOC 2 Type II security, APIs and click‑thru auditability so numbers can be traced back to filings, and the team recently announced a growth round alongside the rebrand to Fiscal.ai (Fiscal.ai terminal features and pricing) that underpins continued product rollout and data expansion (rebrand and Series A details: FinChat rebrand to Fiscal.ai Series A announcement).

The conversational interface can compress an hour‑long earnings call into minute‑ready insights, dashboards and alerts - making it a pragmatic, budget-friendly option to pilot AI‑assisted fundamental research.

“Strongly endorse Fiscal.ai.” - Ernest Wong, Head of Research, Baskin Wealth

Rogo brings a secure, finance‑first generative‑AI workbench that speaks directly to Brazil's deal desks and PE teams by combining custom‑trained LLMs, single‑tenant deployment options and auditable sources so sensitive memos and valuation models never have to leave a controlled environment - see the platform's enterprise features on the Rogo enterprise AI product page.

Built to automate repetitive outputs bankers hate (slide decks, company profiles, market news runs and investment memos), Rogo promises to turn “days of prep” into minutes and fast‑track deal workflows while letting firms choose strict data isolation and SOC/ISO controls; AWS and Google Cloud integrations also underline its secure deployment choices for regulated customers (read the AWS Bedrock compliance case study for Rogo).

"Our strategic integration of Rogo transforms how we deliver value to clients. Rogo enables our teams to analyze market data and identify opportunities with unprecedented speed and precision..." - Patrice Maffre, International Head of Investment Banking, Nomura

For Brazil's Excel‑centric finance teams, Datarails reads like a practical upgrade: keep familiar spreadsheets while outsourcing consolidation, month‑end reporting and variance analysis to an AI layer that understands real company numbers.

Its FP&A Genius brings conversational AI over live, consolidated data so analysts and non‑finance execs can ask natural‑language questions and get instant, traceable answers; Storyboards turn dashboards into board‑ready slides in two clicks, and “fast finance requests” promise answers in about 60 seconds - useful when São Paulo‑based CFOs need last‑minute clarity before a board or regulator call.

Built to automate repetitive processes (consolidation, forecasts, scenario modeling and drill‑down variance work) without ripping out existing Excel models, Datarails often surfaces the “what, why and what's next” for KPIs and can free up days of manual reconciliation - a practical fit for Brazilian firms migrating toward governed, AI‑assisted FP&A (see the Datarails platform and the Datarails FP&A Genius overview for details).

“With Datarails, we save anywhere between two to five full working days per month. Amazing!” - Jens Stottmann, CFO

Workday Adaptive Planning brings enterprise-grade, continuous planning to Brazil's finance teams by embedding next‑gen AI (Illuminate) into everyday FP&A: predictive forecasting, anomaly detection and a conversational Workday Assistant surface contextually relevant insights and recommended actions so teams can model the impact of tariffs or run multiple what‑if scenarios across finance, workforce and operations without rebuilding spreadsheets; its driver‑based models and fast integrations with ERPs and HCMs make rolling forecasts practical for multi‑entity Brazilian groups, and Workday's published deployment cadence (average ~4.5 months) makes it a realistic candidate for medium and large pilots that need governance, scale and faster board-ready answers (see the Workday Adaptive Planning overview and the AI for FP&A - Illuminate page for details).

“Workday Adaptive Planning has allowed us to increase engagement and significantly reduce the time spent on the budget process. It's simpler, people are more involved, and it takes a lot less time.”

Anaplan PlanIQ brings model‑driven forecasting to Brazil's finance teams by wrapping AutoML, multiple statistical engines (ARIMA, ETS, MVLR, Anaplan Prophet) and neural methods (DeepAR+, CNN‑QR) into the connected planning models teams already use - so forecasts are not a separate black‑box but a scheduled, auditable action that pushes results back into Anaplan for review and scenario work.

It ingests historicals plus related drivers (inflation, promotions, events and even country holiday calendars), automatically selects or ensembles the best algorithm, and surfaces quality metrics and explainability so planners can trust and compare forecasts rather than guess; typical model runs render in roughly 30–90 minutes and default quantiles (0.1 / 0.9) provide an 80% confidence band for risk‑aware decisions.

For Brazilian groups managing multi‑entity forecasting, tax or seasonal holidays, and tighter regulator scrutiny, PlanIQ's scheduleable predictions, data‑validation checks and cloud connectors (AWS/Azure/GCP) make it practical to scale AI forecasts without a full data‑science team - see the Anaplan PlanIQ overview (features) and the Anapedia guide to embedding intelligent forecasting into planning cycles.

For Brazil's finance teams that want agentic AI without burning down existing processes, Pigment delivers a practical bridge: a trio of AI agents - Analyst, Planner and Modeler - that proactively analyze trends, turn insights into scenario-ready plans and autonomously build or update the underlying models so spreadsheets stop breaking workflows.

The Analyst continuously surfaces drivers and variance explanations in dashboards, reports or even audio; the Planner runs scheduled forecasts and trade‑offs; and the Modeler fixes formulas and data‑quality gaps so consolidated plans stay board‑ready - imagine a demand planner who no longer spends Sunday nights reconciling numbers because the Planner and Modeler have already prepared an updated forecast.

Pigment also bundles AI Search, Predictions and API connectors to keep ERP/CRM feeds live and secure, and its agentic approach is designed to compress planning cycles from days to hours while preserving visibility and governance; see the Pigment AI agent overview and the Pigment company announcement and demo.

“AI is evolving and so is our ability to equip teams with innovative tools that empower extraordinary outcomes. As we enter this agentic era, we are transforming the dynamics of business operations by seamlessly integrating AI agents into traditional workforces.” - Eléonore Crespo, co‑CEO and co‑founder, Pigment

Databricks functions as a finance-grade lakehouse that lets Brazilian treasury and FP&A teams unify messy GL, ERP and market feeds into governed “gold” tables, run repeatable MLOps and serve certified models and forecasts to dashboards - all on a single platform that combines Delta Lake, MLflow and Unity Catalog for traceability and fine‑grained access control.

Its MLOps guidance shows how to move experiments through development, staging and production with MLflow tracking, scheduled or triggered retraining and automated validation so a cash‑forecast model can be re‑scored and deployed overnight rather than rebuilt every month (Databricks MLOps workflow documentation (MLflow)).

For data teams that need low‑latency feeds and reliable ETL, Lakeflow's declarative pipelines and Delta Live Tables simplify ingestion, lineage and medallion (bronze→silver→gold) processing so BI and regulatory reports run from a single source of truth (Databricks Lakehouse data engineering product page (Delta Live Tables)).

And because orchestration lives natively in the lakehouse, Databricks Workflows reduces brittle handoffs - meaning fewer late‑night firefights before board meetings and faster, auditable answers when regulators or auditors ask for model provenance (Databricks Workflows orchestration blog (lakehouse)).

Hebbia is built for the exact kind of heavy, document‑driven work that Brazil's deal desks, legal teams and asset managers still do by hand: its Matrix/semantic‑indexing engine ingests terabytes of PDFs, DOCX and transcripts, keeps an “infinite” context window across millions of pages, and returns answers with precise, citable passages so auditors and regulators see the source (see Hebbia's engineering write‑up on “Goodbye RAG”).

That focus on multi‑document reasoning makes queries like “find all change‑of‑control clauses across 10,000 pages” or “flag litigation disclosures mentioning supplier concentration” practical in minutes rather than weeks, cutting diligence time and shrinking audit surface for LGPD‑sensitive uploads; product reviews note its strengths on dense filings, expert‑call transcripts and table extraction while emphasizing enterprise controls and encryption (read a concise platform overview and use cases at Dhiwise).

For Brazilian finance teams weighing tools, Hebbia's combination of traceable citations, multi‑agent workflows and enterprise security positions it as a specialist search engine for regulated, text‑heavy workflows where precision and provenance matter more than generic chatbots.

Choosing, piloting and governing AI in Brazil's finance sector starts with rules, not buzzwords: align pilots to LGPD principles, document model inventories and DPIAs, and design human‑in‑the‑loop controls so automated decisions meet Article 20 expectations and remain explainable.

Prioritize vendors that offer data isolation or single‑tenant options and clear contractual promises not to use client data for model training, run regular transparency and fairness checks, and treat the ANPD's findings on generative AI as a living checklist - especially around web‑scraping risks, minors' data and the chain of responsibility for prompts and outputs.

For regulated pilots, consider engaging ANPD's Regulatory Sandbox to test real workflows under supervision; pair technical controls with a governance cadence (inventory → DPIA → pilot → independent audit) and a skilling plan so finance teams can translate AI outputs into defensible decisions.

Practical training matters: teams can learn prompt design, governance and workplace AI skills through targeted courses like Nucamp AI Essentials for Work syllabus (15-week bootcamp) to turn pilot results into board‑ready, auditable practice.