Private-by-default software company
Fintelligent builds local-first consumer and financial intelligence products—and is developing a privacy-focused mobile operating system.
Products ship independently today. Shared private-by-default primitives compound toward the system layer.
Verified execution
Product portfolio
Every product is labelled by what exists now—not by what we hope an investor will assume.
Live on Google Play
A digital-wellbeing app that turns deliberate pauses into healthier app use—without outsourcing the core experience to a cloud account.
Flagship demonstration
Fintelligent Analysis is our flagship deterministic diligence product. This 56-second walkthrough uses synthetic data to show local ingestion, fixed checks, evidence gates and decision-ready exports.
Privacy architecture
Fintelligent is designed around a simple boundary: if we do not need to receive a user's data, we should not build a server that collects it.
Financial statements, trial balances, analytical inputs and generated outputs are processed on the user's Windows device. Fintelligent does not receive, warehouse or claim ownership of that data.
U&AI is built as an encrypted on-device conversation archive. The archive stays with the user; Fintelligent does not operate a conversation database or acquire rights over its contents.
The boundary matters: platform services a user chooses—such as an app store, advertising service, market-data source or AI provider—may process data under their own policies. Fintelligent makes those external boundaries explicit instead of presenting them as our private infrastructure.
Product constitution
Different products have different boundaries. The shared discipline is making those boundaries explicit and inspectable.
Do not collect data simply because infrastructure makes collection possible. Local processing is the default where the product allows it.
Using a Fintelligent product does not transfer ownership of source documents, conversations, watchlists or analytical outputs to us.
When analysis affects decisions, deterministic calculations and source-bound evidence matter more than fluent output.
Products should offer understandable controls, export paths and deletion choices instead of silent lock-in.
Founder-market fit
Skandhaprakash Murali brings 13+ years across FP&A, financial diligence, controls, reporting and process transformation—and turns that operating judgement into working software.
The implementation is AI-assisted. The product logic, financial methodology, architecture decisions and acceptance standards remain founder-owned.
Capital thesis
Grow WePause, release U&AI, improve Investor Lens and convert financial-analysis demonstrations into paid discovery.
Harden local storage, consent, export, identity and on-device intelligence components across the portfolio.
Prove the Privacy OS baseline through reproducible build, boot and device testing before expanding device support.
Pre-seed conversations
Fintelligent is opening conversations with investors and strategic operators who understand privacy, mobile platforms, consumer software and financial intelligence.
Start a conversation ↗Read the investor overview →