Understand
AI understands enterprise data, relationships, policies, manuals, feedback, and business context automatically—no manual data modeling required.
Detect financial leakage, uncover fraud, and identify compliance gaps—with explainable, audit-ready findings.
THE ENTERPRISE RISK CHALLENGE
MEET FORETALE.AI
foretale.ai autonomously understands your enterprise data, plans and executes specialized risk analytics, uncovers explainable findings with supporting evidence, and generates audit-ready reports.
HOW IT WORKS
Designed to augment risk, audit, finance, and compliance teams—experts stay in control while AI executes the analysis.
AI understands enterprise data, relationships, policies, manuals, feedback, and business context automatically—no manual data modeling required.
AI plans the optimal analytics strategy based on your business context.
Execute hundreds of risk analytics across millions of transactions—without manual scripting.
Explainable findings, executive dashboards, and audit-ready reports.
CAPABILITIES
Purpose-built analytics across the risk domains that matter most.
MARKET CONTEXT
Available tools provide transactional risk analytics. Foretale brings the entire engagement together on one AI-powered platform.
WHY FORETALE.AI
Connect your data. Assess risk. Deliver audit-ready findings—all on one autonomous AI platform.
Execute hundreds of risk analytics—and instantly generate customized analytics as business needs evolve. No coding required.
Every finding explained with complete audit evidence.
On-prem, your cloud, or managed SaaS
PRODUCT
From enterprise data to evidence-backed findings—an autonomous path your experts can audit.
FOUNDATION
Methods forged in real advisory work—not theoretical AI demos.
Years of combined experience across Big 4s and super majors — with battle-tested methods from complex forensic engagements.
Fully AWS-native hyperscaler stack — built and run entirely on Amazon Web Services, with strong data safety, security controls, and AI governance in place.
State-of-the-art foundational models powering analysis and reasoning.
Validated on real-world datasets through enterprise pilots.
PRICING
Every engagement is a little different. Share whatever you can below — only a work email is required — and we’ll thoughtfully prepare pricing with an ROI view for your scope. No obligation.
RESOURCES
Articles and frameworks grouped by process area—Accounts Payable, Procurement, Travel & Expense, Order-to-Cash, General Ledger, and programme design.
Leakage and control risks in procure-to-pay and vendor payments.
Article
Duplicate Payment Detection Needs 15+ Analytics
One duplicate-payment rule is not enough. Learn the scenarios that cause leakage, how to turn them into analytics, and how foretale.ai builds those tests.
Article
8 Vendor Master Analytics Every Company Should Run
How AI finds duplicate suppliers, shared bank accounts, and master-data gaps before they become payment leakage.
Article
What AP Actually Paid.
PO ordered 100. Goods received 40. Invoice cleared 100—seven analytics that catch the gap.
Article
New Vendor. Big First Payment. Then Nothing.
Vendor added Day 0. Paid Day 3. Next bill never—seven checks that catch rush vendors.
Article
Same Vendor. Too Many Invoices.
Peer vendors send 4 invoices a month. This one sent 47—seven checks that catch unusual volume.
Fake competition, collusion, and award risks that inflate cost before the invoice hits AP.
Article
Three Suppliers. One Bank Account. The Bid Was Never Competitive.
How shared vendor identities expose bid rigging—and seven analytics that catch fake competition.
Article
Vendor Relationship Networks.
Two vendors never share a bank account, tax ID, or phone—yet they always bid together. Build a graph instead of rule-based analytics.
Behavioral risk in T&E—beyond policy gates and sampled audits.
Article
Stop Looking at Expense Reports. Start Looking at Expense Behavior.
Why traditional expense audits miss the highest-risk transactions—and how AI changes the game.
Article
Personal Shopping. Business Expense Code.
Seven analytics that catch shopping, lifestyle, and home-city spend submitted as business.
Article
Same Dinner. Three Claims.
Meal total 9,600. Approval above 5,000. Submitted as 3,200 + 3,200 + 3,200—seven checks that catch split expenses.
Post-termination pay, ghost employees, and payroll master gaps that drain salary spend.
Article
The Badge Was Deactivated. The Salary Kept Clearing.
How payments after termination and payroll master gaps create silent leakage—and eight analytics that catch it.
Article
On Payroll. Nowhere in the Building.
How ghost employees hide in payroll—and eight analytics that expose fictitious, duplicate, and no-show workers.
Misuse and leakage risks in P-Card programs—beyond monthly statements and sampled receipts.
Billing, credits, pricing, and collection risks that quietly erode revenue.
Article
7 Order-to-Cash Analytics Every Company Should Run to Protect Revenue
How AI helps identify billing errors, revenue leakage, duplicate credits, and collection risks before they impact the bottom line.
Article
The List Price Was Fine.
Policy capped the discount at 5%. The invoice took 18%—seven analytics that catch Order-to-Cash discount leakage.
High-priority journal and balance risks in the books of record—beyond trial-balance sampling.
Reference guides for structuring enterprise risk and compliance analytics programmes.
FAQ
Clear answers about foretale.ai—built by HEXANGO for enterprise risk, audit, finance, and compliance teams.
foretale.ai is an autonomous AI risk analyst from HEXANGO. It understands enterprise data, plans and executes specialized risk analytics, and produces explainable findings with audit-ready reports.
It helps teams detect financial leakage, uncover fraud, and identify compliance gaps across ERP and transaction data—without building custom scripts for every test.
The platform follows Understand → Plan → Execute → Explain: it learns your business context, plans analytics, runs risk tests at scale, and returns evidence-backed findings your experts can review.
Risk, audit, finance, and compliance teams that need broader coverage, faster assessments, and lower cost than manual analytics or fragmented tool stacks.
Yes. The Understand step maps enterprise data, relationships, policies, manuals, feedback, and business context automatically—so teams do not need to build or maintain manual data models before analysis can start.
It ingests and interprets ERP and related transaction datasets in a dedicated workspace, learns how entities and processes relate, and keeps analytics aligned to that context as you assess risk across large volumes of enterprise data.
You can execute hundreds of risk analytics across millions of transactions and generate customized analytics as business needs evolve—without writing scripts or rebuilding a new pipeline for every test.
Yes. Results surface in executive dashboards and audit-ready reports. Custom visualizations are available as an option on Pilot and Professional plans, and are included on Enterprise.
Yes. Findings move from detection into investigation workflows so teams can validate, escalate, track, and close cases with evidence—replacing fragmented BI, copilot, case management, and reporting tool stacks.
Yes. Teams can ask questions of their data in plain language—for example to find duplicate payments or explain a top case—and receive evidence-backed answers tied to the underlying transactions.
Yes. Every finding includes supporting evidence and lineage so experts can trace how a conclusion was reached and produce audit-ready reporting.
foretale.ai runs on an AWS-native stack with encryption in transit and at rest, dedicated workspace isolation, least-privilege access, and security controls aligned to our Information Security and Access Control policies.
Professional plans run as managed SaaS. Enterprise supports SaaS, private cloud, or on-prem so data residency and architecture can match your security requirements.
No. Customer content is not used to train third-party foundation models. AI features use only data authorized for the authenticated user and project, with session- and organization-scoped context.
AI assists professional judgment—it does not replace it. We apply human oversight, Bedrock Guardrails, bias and safety reviews, and documented limitations. Details are in our Responsible AI Policy and AI Transparency Statement in the Trust Center.
Yes. Findings are explainable with supporting evidence. Users can inspect reasoning and sources where available, and high-impact actions require human authorization before changing customer data.
Access uses authenticated accounts (Amazon Cognito), role-based authorization, and least privilege. Organizations control who can see which projects and data within their dedicated workspace.
Our Trust Center publishes policies on information security, access control, incident response, data retention, responsible AI, AI transparency, vulnerability disclosure, and architecture at hexango.com/trust-center.
Personal data is handled under our Privacy Policy. Retention and secure deletion follow project and contractual settings described in the Data Retention Policy—customers control how long operational data is kept.
Plans include a free assessment, Pilot ($14,900 one-time), Professional ($38,900/year), and custom Enterprise. Implementation starts at $8,900.
NEXT STEP
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BROCHURE
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