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AI Solutions

From operational challenge to working solution.

PGI turns complex requirements into clear business cases, practical designs and solutions that reach operational use — combining AI where judgement adds value with dependable automation for repeatable steps, and people wherever approval matters.

What PGI delivers

Two connected services.

02

AI Opportunity & Solution Design

Translate operational challenges into clear business cases and practical solution designs.

Deliverables

  • Opportunity assessment and prioritisation.
  • Benefits, costs and assumptions.
  • Process, data and integration requirements.
  • Solution architecture and delivery roadmap.
  • Proof-of-value scope and success criteria.
03

Complex AI Delivery & Digital Workforce

Guide solutions from initial validation into operational use, working with your teams and appropriate delivery partners.

Scope

  • Enterprise integration.
  • Digital workers and business process automation.
  • Human approvals and exception handling.
  • Secure knowledge access.
  • Adoption, operational ownership and outcome measurement.

PGI leads design and coordinates delivery. Build capacity comes from your own teams and appropriate delivery partners — PGI does not present itself as a large in-house implementation team, and selects partners for the work at hand.

How complex requirements are approached

Design considerations, worked through for every solution.

These are the questions PGI works through with your teams. They are design considerations for each engagement, not blanket certifications or guaranteed capabilities.
  1. 01

    Connecting to existing business systems

    Most value sits in systems you already run — ERP, CRM, case management, document stores. Designs start from how those systems expose data and accept updates, and what that means for reliability.

  2. 02

    Working with sensitive information and access controls

    Who may see which documents, records and answers is defined up front and enforced in the design, not left to the model. Access follows existing roles wherever possible.

  3. 03

    Selecting cloud, private or edge deployment approaches

    Where models and data run is a design decision shaped by data residency, latency, cost and the systems involved. Public cloud, private hosting and edge deployment each have a place.

  4. 04

    Designing human approvals and escalation

    Each workflow states which steps a person confirms, what they see when they do, and how exceptions and disagreements are escalated and recorded.

  5. 05

    Evaluating reliability, operating costs and support needs

    Before scaling, the solution is assessed for accuracy on real cases, running cost at expected volumes, failure modes, and who supports it once live.

  6. 06

    Preparing teams to adopt changed workflows

    A working solution that nobody trusts delivers nothing. Adoption planning, training and feedback loops are part of the design from the beginning.

Illustrative workflows

What a digital worker does — and where people stay in control.

Software that carries out defined business tasks across systems, with people involved where judgement or approval is required. The examples below are illustrative designs, not screenshots of live customer systems.
Supplier invoice exception handlingIllustrative example
  1. 1. Trigger

    Supplier invoice arrives

    PDF received in the accounts-payable mailbox.

  2. 2. Digital worker

    Extract and match

    Reads the invoice, finds the purchase order and compares quantities, prices and terms.

  3. 3. Enterprise system

    Check the finance system

    Looks up goods received and supplier status; posts automatically when everything matches.

  4. 4. Human approval

    Accounts payable reviews exceptions

    Mismatches are presented with the evidence. A person approves, queries or rejects.

  5. 5. Outcome

    Recorded and closed

    Supplier informed, record updated, decision logged.

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Trigger
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Digital worker
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Enterprise system
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Human approval
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Outcome

Measures to assess: proportion of invoices posted without manual touch, exception resolution time, error rate on posted invoices.

Customer enquiry with approved knowledgeIllustrative example
  1. 1. Trigger

    Customer enquiry received

    Web form, email or contact-centre note.

  2. 2. Digital worker

    Classify and prepare

    Identifies the request type, retrieves the customer record and relevant approved guidance.

  3. 3. Enterprise system

    Draft using policy

    Drafts a response from approved knowledge, with citations to the source documents.

  4. 4. Human approval

    Agent confirms or edits

    Routine cases are confirmed in one step; anything involving a concession goes to a team lead.

  5. 5. Outcome

    Reply sent, case updated

    Turnaround and edit rates tracked for review.

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Trigger
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Digital worker
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Enterprise system
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Human approval
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Outcome

Measures to assess: time to first response, proportion of drafts sent unedited, escalation rate, service quality.

The path from idea to operation

Use AI where interpretation and judgement add value, and dependable automation for repeatable steps.

  1. 01

    Identify

    Understand the process, pain points and business priorities.

  2. 02

    Assess

    Establish potential value, feasibility, costs and risks.

  3. 03

    Design

    Define the workflow, architecture and human responsibilities.

  4. 04

    Prove

    Validate a focused use case against agreed measures.

  5. 05

    Scale

    Integrate, support adoption and track performance.

Industry examples

Where these patterns apply.

Illustrative applications across six sectors. Each shows the operational challenge, where AI and automation could help, the human oversight required and the measures to assess. They are not a list of completed customer deployments, and no savings or outcomes are claimed.

The operational challenge

Onboarding, servicing and claims teams handle high volumes of documents and enquiries under strict controls on who can see what and how decisions are recorded.

Customer onboarding, document processing, servicing, claims workflows and controlled access to operational knowledge.

Human oversight

Decisions with financial or regulatory consequences remain with named people. Automation prepares, checks and routes; it does not approve.

How AI and automation could help

  • Extracting and checking information from onboarding documents before a case reaches an underwriter or analyst.
  • Preparing claims files by gathering policy details, correspondence and supporting evidence in one place.
  • Answering servicing questions with controlled access to product rules and operational procedures.

Measures to assess

  • Case turnaround time
  • Rework and error rates
  • Time to first response
  • Audit completeness

Technology partnership

PGI is a Greentic partner.

PGI is a Greentic partner, helping organisations explore and implement digital workers that connect business processes, enterprise systems and human approvals.

Greentic provides a platform for building and running digital workers. Where it fits the requirement, PGI designs and delivers with it. Where a different approach suits better, PGI says so — every engagement is designed around your systems and priorities, not around a single product.

Explore Greentic

What the partnership supports

  • Digital workers that connect business processes across enterprise systems.
  • Human approvals and exception handling built into each workflow.
  • Controlled access to operational knowledge.
  • Adoption, operational ownership and outcome measurement.

What is a digital worker?

Software that carries out defined business tasks across systems, with people involved where judgement or approval is required.

Which operational challenge would you start with?

Bring a process, a backlog or a pilot that has stalled. We will discuss what a practical design and route to operation could look like.

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