AI overlay for payment stacks Gateway · Aggregator · Fintech

See every payment with more context.

CogniView adds a thin AI layer over your existing gateway or routing setup – giving you smarter approvals, clearer risk and transparent insight without breaking your current flow.

Built for India-first and global payment flows • Email: support@cogniview.in

Risk scoring at transaction level Lightweight scores and explanations you can log, audit and tune with your own rules.

Routing hints you can override AI suggests best routes, you keep final control with your existing routing engine.

Signals for product and ops teams Pattern views for chargebacks, failures and behaviour – not just raw logs.

Sample AI overlay snapshot

For demo only

Risky attempts (last 24h)

2.7%

Flagged with reasons

Approval uplift (AI routes)

+1.9 pts

Controlled A/B view

Chargeback-prone BINs

Auto-updated list

Unusual behaviour clusters

For manual review

Step 1: Existing gateway sends light metadata stream to CogniView.

Step 2: AI returns risk hints, route hints and simple tags in milliseconds.

Step 3: Your engine decides. CogniView is advisory, not a hard blocker.

We do not replace your gateway or bank partners.
CogniView sits as an intelligence layer – reading your streams, learning patterns and sending back small, useful signals.

Gateway-agnostic Work with your current PSPs and acquirers.

Explainable Keep reasons for every score and hint.

Control in your hands Full override at your own rule engine.

Use cases

Where CogniView helps inside your payment flow

Different teams see different benefits – but everything comes from the same AI layer, reading the same transaction and behaviour data in real time.

Transaction-level risk hints

Lightweight risk scores with simple reasons like “new device + high ticket + known risky BIN”. You choose how to react inside your routing or rule engine.

Score + reason Log-friendly

Approval uplift with safer routing

AI suggests alternate acquirers or routes when patterns show better approval for a similar card mix or geography. Final decision is still yours.

Contextual routing hints A/B comparison

Chargeback and dispute patterns

See which combinations of BIN, merchant type, time band or device are driving most disputes – not just a raw list of chargeback IDs.

Hotspot views Ops dashboards

Behaviour clusters and anomalies

Detect group-level patterns like repeated small attempts before a big ticket, or sudden changes in typical geography mix.

Anomaly flags Review queues

How it works

Simple flow from your gateway to CogniView and back

This is the typical journey we follow for most clients. Exact steps and data fields will be finalised with your tech and compliance teams.

Phase 1

Read-only shadow mode

We first connect in a read-only way – only reading logs / events. No impact on live routing or approvals. Models learn from your real traffic quietly in the background.

Phase 2

Advisory mode with internal view

Once signals are stable, we expose a simple view and APIs for your team. You can see scores, hints and patterns, but do not act on them automatically yet.

Phase 3

Controlled action hooks

Finally, you connect CogniView outputs to your routing and rules. You start with small slices of traffic and expand only after you are confident.

Impact

What teams usually aim for with CogniView

Numbers will differ by business and risk appetite. These are typical goals we discuss at pilot stage, not promises.

+0.5–2.0 pts Improvement in approval rate on selected traffic, without loosening risk rules.

10–25% Better concentration of manual review on truly unusual patterns.

Clear view For product, risk and ops teams on why certain flows behave differently.

Single layer Shared AI signals across web, app, subscription and in-app flows.

Sample stories

Examples of how CogniView can be used

These are indicative story types. Actual results will depend on your data, volume and policy choices.

Gateway

Routing hints reduce overnight retries

A gateway saw better late-night approvals on a specific acquirer. CogniView started suggesting that route only for similar BIN + time combinations, bringing uplift without hurting risk.

Fintech

Repeat fraud pattern caught early

Behaviour clustering highlighted a small set of devices and IPs that kept testing new merchants. Risk team was alerted before losses became large.

SaaS

Chargeback view helps product decisions

By seeing which user segments created more disputes, the SaaS company could tweak onboarding and product flows, not just payment rules.

Contact

Share your payment stack and challenges

Send us a simple outline of your payment flow and what you want to improve. We will reply with possible pilot options and data needs in clear language.

You can write directly to support@cogniview.in or use the form here.

It helps if you can share:

Whether you are a gateway, aggregator, fintech, NBFC or merchant.
Basic picture of your payment routing and log setup.
Which metric you care about most (approvals, fraud, disputes, ops effort).

We will keep the first conversations simple – no heavy jargon, no pressure. Just a clear view of what is realistically possible on top of your current stack.