seKer AI
Typical scenarios

How we approach common briefs

These are illustrative engagement patterns. They are not published as completed client case studies and do not include invented metrics.

Financial operationsIllustrative

Real-time transaction monitoring

Problem

A rules-only review process struggles as transaction volume grows: too many false alarms for legitimate users, and still not enough signal on unusual behavior.

Approach

A scoring service that combines model output with operator review, so unusual activity can be inspected without treating every exception as a hard block.

Implementation

A streaming or near-real-time path into a model service, plus a review console the partner’s team can operate and extend.

Designed to support

  • Faster review of unusual activity
  • Fewer interruptions to ordinary users
  • A workflow operators can inspect
  • A service that fits existing payment or ops systems
Retail operationsIllustrative

Demand planning across many SKUs

Problem

Inventory planning is too coarse. Teams over-order in some places and miss demand in others because the useful history is not modeled at the right grain.

Approach

SKU- or location-level forecasting that can take seasonality, promotions, and the partner’s existing planning process into account.

Implementation

A model pipeline with a review surface, designed to feed the systems the operations team already uses rather than replace them overnight.

Designed to support

  • Planning at a more useful grain
  • Fewer stock and overstock surprises
  • A forecast the team can question
  • A path into existing ERP or ordering tools
SaaS productsIllustrative

Support deflection with retrieval

Problem

Support volume grows with the product. The answers often already exist in docs, but agents and users still open tickets for the same questions.

Approach

A retrieval-backed assistant that answers from current documentation and hands off when the case is unclear or high-risk.

Implementation

A RAG service over product knowledge, deployed in the channel the partner already uses, with analytics the support lead can review.

Designed to support

  • Faster first responses on common questions
  • Less repetition for human agents
  • Answers tied to current docs
  • A handoff path that stays under the partner’s control

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