AI Solution Technologies
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Generative AI & Copilot / SUB-PRACTICE 3.320 NEW FOR 2026-27

GenAI Engineering.

Every GenAI Engineering service AI Solution Technologies delivers — 20 in total, within the Generative AI & Copilot practice.

Book a scoping call →See how it runs
Retrieval engineering including chunking, hybrid searchPrompt and context management as controlledModel benchmarking against real client tasksBilingual and multilingual evaluation capability
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MicrosoftAzureAWSGoogle CloudDatabricksSnowflake

The problems GenAI Engineering exists to solve.

Answer quality that varies unpredictably between users and questions
Prompts managed as untracked text scattered across teams
Retrieval that returns plausible but irrelevant evidence
Running cost rising faster than measured benefit

What is GenAI Engineering?

SENIOR-LEDRetrieval and context architecture design
PRODUCTION-READYVersioned prompt library with evaluation results
KPI-DEFINEDModel selection analysis against the client's tasks and constraints

Get a free discovery sprint

Before you commit, we help you confirm the use case, check data readiness, define the KPI, and work out which of the 20 GenAI Engineering services actually fit the problem you have.

For a limited number of teams each quarter, we run the full sprint free of charge.

Claim a free sprint →
THIS SUB-PRACTICE
20SERVICES
20NEW FOR 2026-27
7STAGE DELIVERY

How GenAI Engineering runs.

01
Confirm objectives, stakeholders, constraints and success measures
Review current systems, data, controls and delivery readiness
Prepare the target design, backlog, governance and implementation plan
Test the priority requirements through a prototype, pilot or controlled design review
Configure, integrate, test and deploy the approved solution
Train users, transfer knowledge and establish operating procedures
Monitor adoption, performance, cost, quality and improvement opportunities
KEY CAPABILITIES

What we bring to GenAI Engineering.

  1. 01Retrieval engineering including chunking, hybrid search and re-ranking
  2. 02Prompt and context management as controlled assets
  3. 03Model benchmarking against real client tasks, not public leaderboards
  4. 04Bilingual and multilingual evaluation capability
  5. 05Cost engineering across model routing, caching and quotas

What you get, and what follows

DELIVERABLESRetrieval and context architecture designVersioned prompt library with evaluation resultsModel selection analysis against the client's tasks and constraintsCost model with optimisation recommendationsEvaluation framework and baseline scoresEngineering documentation and knowledge transfer
BUSINESS OUTCOMESMaterially higher answer accuracy on the tasks that matterPredictable, attributable running costChanges released with evidence rather than by assumptionReduced dependency on any single model providerAn engineering practice the client's own team can maintain

The 20 services inside GenAI Engineering.

20 SERVICES · 20 NEW
Prompt Engineering & Prompt Library ManagementNEWDevelopment, testing and central management of production prompts as versioned, reviewable assets rather than ad-hoc text.Prompt Versioning & RegistryNEWA controlled registry recording every production prompt, its version, its owner, its evaluation results and its release history.Context Engineering & Window OptimisationNEWDesign of what information is placed in front of a model, in what order and at what cost, to maximise answer quality.Retrieval Architecture DesignNEWDesign of chunking, indexing, hybrid search, filtering and re-ranking so retrieval returns the right evidence for the question asked.Vector Database ImplementationNEWSelection, deployment and tuning of vector search infrastructure such as Azure AI Search or pgvector within the client's environment.Embedding Model SelectionNEWEvaluation and selection of embedding models against the client's content, languages and retrieval accuracy requirements.Knowledge Graph Construction for GroundingNEWConstruction of an entity and relationship graph over enterprise content so generative AI can reason across connected facts.GraphRAG ImplementationNEWRetrieval-augmented generation over a knowledge graph, enabling multi-hop questions that vector search alone cannot answer.Multimodal AINEWImplementation of AI over documents, images, audio and video in addition to text.Document Intelligence & Intelligent Document ProcessingNEWExtraction and validation of structured data from complex documents including forms, contracts, drawings and scanned records.Conversational & Voice AINEWDesign and delivery of voice and conversational interfaces integrated with enterprise systems and human handover.Arabic-English Bilingual AI Evaluation & TuningNEWEvaluation, tuning and quality assurance of AI systems operating in Arabic and English, covering accuracy, tone, dialect and cultural appropriateness.Model Selection & BenchmarkingNEWStructured comparison of candidate models against the client's tasks, data, latency, cost and sovereignty requirements.Small Language Model & Edge DeploymentNEWDeployment of smaller models on constrained, disconnected or privacy-sensitive infrastructure.Model Fine-Tuning, LoRA & DistillationNEWAdaptation of models to a client's domain, terminology and task set where prompting alone is insufficient.Model Routing & FallbackNEWAutomatic routing of requests between models by task complexity, cost and availability, with graceful degradation.LLM Gateway & API ManagementNEWA central, governed gateway for all model access providing authentication, quota, logging, cost attribution and policy enforcement.Semantic CachingNEWCaching of semantically equivalent requests to reduce inference cost and latency without degrading answer quality.Token Cost Optimisation & GenAI FinOpsNEWMeasurement and reduction of generative AI running cost by workload, team and use case, with chargeback and forecasting.A/B Testing & Experimentation for GenAINEWControlled experimentation infrastructure that measures whether a prompt, model or retrieval change actually improves outcomes.
INVESTMENT & DELIVERY

How we engage on GenAI Engineering.

INDICATIVE VALUE
A$60,000 – A$250,000A$15,000 – A$60,000A$250,000 – A$1,200,000Monthly retainer, A$7,500 – A$25,000 per month
The bands across these 20 services. Each service page carries its own; the scoping call confirms the range for your environment before anything is committed.
DELIVERY MODELS
Fixed price or milestone basedFixed priceMilestone based, or time and materials for evolving scopeManaged-service retainer with agreed service levels
Delivered by a senior-led Australian team across 7 stages, from discovery through to optimisation.Discuss scope and timing ›
WHO THIS IS FOR
  • Banks, insurers, superannuation funds and professional-services firms
  • Government agencies and regulated public-sector bodies
  • Large enterprises and mid-market organisations undergoing modernisation
  • Utilities, energy and resources operators

What our customers say.

All customer stories
"Reconciliation that took our team nine days now closes in three — with a full audit trail on every match. It changed how the board sees AI.
Finance ManagerGCC Construction Group, Dubai
"Site teams stopped digging through folders. They ask the assistant, they get the clause with a citation, and they move on.
Project DirectorTier-One Contractor, Sydney
"The anomaly models flag outliers the week they appear, not at quarter-end. We stopped two overruns before they hit the P&L.
Commercial DirectorProperty Developer, Dubai
"Seven subsidiaries of spreadsheets became one governed reporting platform. The executive finally trusts the numbers on the screen.
Group CFOInfrastructure Holding, Riyadh

Our partnerships with
industry leaders

MicrosoftSolutions Partner
Google CloudPartner
SalesforcePARTNER
AWSpartner
network

Elsewhere in Generative AI & Copilot.

The whole practice →

Scope GenAI Engineering in one call.

Tell us the problem. We'll tell you which of the 20 services fit — and exactly how we'd deliver them.

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