Make sense.
Then make something.
Applied AI and product teams.
From ambiguous questions to working products.
Applied AI and product teams.
From ambiguous questions to working products.
01 / EXPERIENCE
Decades of hands-on work in financial services, carried into applied AI for product teams everywhere else.
Fintech depth
Across lending, payments, and BNPL books.
Models that price risk from real repayment behavior, not just bureau scores.
Onboarding pipelines that clear genuine customers in minutes, not days.
Signals that catch bad actors without punishing good customers.
Prioritization that recovers more while treating borrowers fairly.
Portfolio-level views that hold up in front of risk committees and regulators.
Beyond fintech
Applied AI for product teams across verticals.
Production systems that turn foundation models into dependable product features.
Structured meaning from messy text and transactions, at scale.
Models and agents that take repetitive operational work off teams' plates.
Assistants that speak in the client's own voice and stay honest under evaluation.
02 / WORK
Our own product, and a sample of client engagements.
A product we built ourselves: a vernacular assistant that helps women find the government schemes they qualify for, and then manage the money those schemes bring in.
With her consent, her bank data is shared read-only through an Account Aggregator partner. Aitera is not itself an Account Aggregator. The product turns it into plain-language insight, such as a missing scheme payment and how to claim it. A voice assistant answers in her own language, and a grounded scheme knowledge base for Tamil Nadu and Karnataka explains eligibility, documents and which office to visit. The Account Aggregator connection is planned; the product is pre-launch.
For an Indian B2B fintech provider in the RBI-licensed Account Aggregator ecosystem: an engine that turns raw bank-statement narrations into structured financial categories - income, EMIs, utilities, lifestyle, transfers, investments.
A fine-tuned LLM reads each narration, retrieval over a merchant knowledge base resolves ambiguous merchant names, and a rules layer keeps categories consistent across crores of rows. Banks, NBFCs, wealth managers, and fintech apps run credit underwriting, debt-to-income assessment, fraud detection, and personal-finance dashboards on the output.
CASE STUDYFor a coaching business: an AI coaching companion that speaks in the coach's own voice, built from an archive of raw recordings into a working product.
Conversation flows are grounded in the coach's material through retrieval over session transcripts, a custom voice pipeline reproduces the coach's delivery, and an evaluation loop scores every answer against the source material.
CASE STUDYFor a Middle East-based stablecoin payment platform: AML and compliance tooling for digital-asset money movement.
Transaction monitoring tuned to on-chain patterns, risk scoring on counterparties and flows, sanctions screening, and the reporting pipeline regulators expect - built into the payment path, not bolted on.
CASE STUDYFor a family office: an AI assistant that gives the relationship manager a daily digest - what moved, what matters, what needs action.
Ingestion pipelines pull news, portfolio data, market events, and KYC/compliance feeds. Entity resolution ties events to holdings, and LLM summarization ranks everything by relevance to the book.
CASE STUDY03 / ABOUT
The phase where business problems are ambiguous, data is messy, and the path to a working product is unclear.
Aitera is a data science and applied AI consulting firm. For teams looking to validate data and AI hypotheses without straining internal bandwidth, we provide the expertise to move fast.
Our team takes ownership of scoping, data pipelines, feature engineering, model development, and integration - delivering testable products ready for alpha and beta feedback.
We operate as a fractional extension of your team, structured to adapt as requirements evolve. Applied AI and product specialists, and forward-deployment engineers, with vertical depth. No junior resources, no learning curves on your timeline.
04 / TEAM
The people behind the work above.
Behind them: a small team of forward-deployed engineers who join engagements as fractional resources.
05 / CONTACT
Every engagement above started as a conversation about an ambiguous problem. Tell us what you're working on; we reply within a day or two.
Talk to us - saimadhu@aitera.in