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Skarp Global

Solutions

Five solution areas. One engineering practice.

Each solution starts from a business problem and connects AI to the data, software and people involved. Most real systems combine more than one.

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01

AI Customer Support Agents

Build AI support agents that understand customer requests, retrieve relevant knowledge, and handle routine interactions while escalating complex cases when needed.

Explore AI customer support

Business problems

  • Support teams spend much of their day on repetitive questions.
  • Customers wait for answers that already exist in policies and help content.
  • Context is lost when conversations move between channels and people.

Example use cases

  • Order, delivery and account questions
  • Policy and product information
  • Ticket triage, tagging and routing
  • Drafting replies for agent review
02

Agentic Commerce Solutions

Make product discovery, shopping assistance, and order journeys more intelligent with AI systems connected to commerce workflows.

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Business problems

  • Shoppers struggle to translate needs into the right search terms and filters.
  • Product information is detailed but hard to compare.
  • Order-status and returns questions take up commerce and support teams’ time.

Example use cases

  • Natural-language product search
  • Guided product comparison
  • Context-aware recommendations
  • Order tracking and returns assistance
03

AI Workflow Automation

Connect business tools and automate multi-step workflows, reducing repetitive work while preserving appropriate approvals and human oversight.

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Business problems

  • Information is re-keyed manually between disconnected applications.
  • Documents arrive in varied formats and need reading before anything can happen.
  • Hand-offs between teams create delays and lost context.

Example use cases

  • Invoice and document processing
  • Request intake and routing
  • Data entry across systems
  • Report preparation and follow-ups
04

Predictive and Decision Systems

Turn business data into forecasts, operational insights, anomaly detection, and decision support.

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Business problems

  • Planning relies on spreadsheets and judgement that is hard to scale.
  • Unusual changes in operations are spotted late.
  • Data exists, but turning it into a decision takes too long.

Example use cases

  • Demand and volume forecasting
  • Anomaly and risk detection
  • Operational dashboards with insights
  • Recommendations for planners

05 · Foundation layer

Enterprise AI Solutions

Integrate AI into your business through knowledge systems, retrieval, software integrations, evaluation, security, and production infrastructure.

Problems it addresses

  • Institutional knowledge is spread across documents, tools and people.
  • AI pilots stall before production because of data, security or quality concerns.
  • Teams want AI assistance but need it to respect permissions and policies.
Explore enterprise AI
Diagram: the four application areas - customer support, commerce, workflow automation and predictive systems - all sit on a shared enterprise AI foundation of knowledge systems, retrieval, software integrations, evaluation, security and production infrastructure.

Applications

  • AI Customer Support Agents
  • Agentic Commerce
  • AI Workflow Automation
  • Predictive systems

Enterprise AI foundation

  • Knowledge systems
  • Retrieval
  • Software integrations
  • Evaluation
  • Security
  • Production infrastructure

The same foundations - knowledge, retrieval, integrations, evaluation and security - support every application area.

Combining solutions

Real problems rarely fit one category

We design the combination around the outcome, not the label. A few examples of how the areas connect:

  • Support + Automation

    Returns handled end to end

    A support agent collects a return request; an automated workflow checks eligibility, issues the label and updates the order system.

  • Commerce + Prediction

    Recommendations that respect stock

    Demand forecasts inform which products a shopping assistant highlights when inventory is constrained.

  • Enterprise AI + Any

    Foundations built once

    A shared knowledge index, integrations and evaluation set can serve several assistants and workflows.

Not sure which area fits?

Describe the problem. We’ll help you work out which combination of AI, data and software is worth exploring.

Discuss your projectContact us

Or email info@skarp.global