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Skarp Global

AI engineering / Intelligent systems

Intelligence, engineered.

We build AI systems that automate work, improve customer experiences, and help businesses make better decisions.

Discuss a projectExplore our solutions

Data, reasoning, action, outcomes.

agent-console / support / run 2841Concept interface
Concept interface showing an AI support agent using connected business data to assess a refund request, preparing the refund, and routing it to a person for approval. Illustrative data.

Connected data

  • Help centreDocuments
  • Order databaseRead only
  • CRMCustomer record
  • HelpdeskHandoff

Support agent

4 steps · 1 awaiting review
  1. Request receivedData

    “My order is late. Can I get a refund?”

    Completed
  2. Context retrievedData

    Refund policy §4 · order #48213 · customer history

    Completed
  3. Eligibility assessedReasoning

    Delivery 6 days late - refund permitted by policy

    Completed
  4. Refund preparedAction

    Amount above auto-approve limit - sent for review

    Awaiting human approval
OutcomeCustomer updated · refund queued for a team lead
Awaiting approval

What we build

Intelligence for real business problems.

AI solutions designed around the way your business works.

  • support / conversationConcept interface
    Concept interface: a customer asks about a late order, the AI agent retrieves the shipping policy and order status, answers, and hands the address change to a human support agent. Illustrative conversation.

    Customer

    My order hasn’t arrived. Can I change the delivery address?

    RetrievedShipping policyOrder #48213

    AI agent

    Your order shipped yesterday and is due Thursday. Address changes after dispatch need our team, so I’ve passed this on with your details.

    Handed to support teamEscalated

    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
  • storefront / shopping assistantConcept interface
    Concept interface: a shopper searches in natural language for waterproof, wide-fit trail shoes under $150, the assistant recommends matching products with reasons, and shows an order status update. Illustrative products and prices.
    Waterproof trail shoes, wide fit, under $150
    • Ridge GTX trail shoeBest matchWaterproof · wide fit$139
    • Fell Runner 3Waterproof · regular fit$124
    Order #48213 · arriving ThursdayIn transit

    Agentic Commerce Solutions

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

    Explore agentic commerce
  • workflows / supplier-invoiceConcept interface
    Concept workflow: an invoice is received by email, fields are extracted, matched against a purchase order in the ERP, sent for finance approval, then entered in the accounting system. Three steps done, approval waiting, final step queued.
    1. Invoice receivedEmailDone
    2. Extract fieldsDocument AIDone
    3. Match purchase orderERPDone
    4. Finance approvalApproverWaiting
    5. Create billAccountingQueued

    AI Workflow Automation

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

    Explore workflow automation
  • insights / demand · product group BExample dataset
    Illustrative chart using an example dataset: weekly demand rises from about 52 to 74 units over 16 weeks, with an unusual spike to 92 in week 14 flagged as an anomaly. A dashed forecast continues to about 81 units over the next six weeks with a widening uncertainty range. A recommendation suggests reviewing the reorder point.
    Actual Forecast Range Anomaly
    Week 14 spike - 92 units vs ~68 expected. Coincides with a regional promotion.
    Recommendation - review the reorder point before week 18.

    Predictive and Decision Systems

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

    Explore predictive systems

Across every solution

Enterprise AI Solutions

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

It is the engineering layer underneath every application above - and a service in its own right for internal knowledge systems and AI assistants.

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

Our product

Storely - our AI commerce agent for online stores

From shopper intent to completed order, in one conversation. Product discovery, offers, basket building, checkout, order tracking and support, on a retailer’s existing storefront.

Visit storelycommerce.com (opens in a new tab)About Storely

Technical approach

Beyond models. Into real workflows.

The value of AI comes from connecting intelligence to data, tools, and decisions.

Trace an example

Data moves through four stages: business data becomes context for the intelligence layer, agents and workflows act on it, and the results show up as business outcomes.

  1. 01

    Business data

    • Documents
    • Databases
    • Internal knowledge
    • Operational systems
  2. 02

    Intelligence layer

    • Models
    • Retrieval
    • Context
    • Evaluation
  3. 03

    Agents and workflows

    • Reasoning
    • Tool use
    • Orchestration
    • Execution
  4. 04

    Business outcomes

    • Customer assistance
    • Automated processes
    • Operational insights
    • Better decisions

Monitoring and evaluation feed results back into the intelligence layer.

Conceptual architecture. Each system uses the components its problem requires.

Engineering principles

Built for the real world.

Useful AI depends on more than a model. It requires thoughtful integration, testing, operational controls, and continuous improvement.

  • 01

    Outcome-led

    Start with the business problem, define the desired outcome, and choose the technology that fits.

  • 02

    System-aware

    Design around existing data, tools, permissions, and operational workflows.

  • 03

    Reliability-focused

    Evaluate realistic scenarios, handle failures, and build in appropriate access controls and human oversight.

  • 04

    Designed to evolve

    Plan for monitoring, evaluation, iteration, and changing business requirements.

About Skarp Global

Practical AI. Thoughtful engineering.

Skarp Global builds AI-powered systems that connect intelligent models with business data, software integrations, and operational workflows. We focus on practical solutions shaped around real business needs.

What we build
AI agents, workflow automation, enterprise AI and predictive systems.
How we work
Discover, design, build and validate, then deploy and improve.
More about Skarp Global

Have a business problem AI could solve?

Let’s understand the challenge and explore what a useful solution could look like.

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Or email info@skarp.global