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INNODRIVE

Research-Driven AI Transformation for Engineering-Intensive Industries

Innodrive applies AI to the business and engineering workflows inside complex organisations. We map how the system works today, find where intelligence changes the outcome, and implement it.

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A · CURRENT STATEB · INTELLIGENCEC · AI-ENABLED WORKFLOWClientArchitectEngineerContractorSupplierSiteDrawingsEmailERPREADCHECKROUTEDRAFTRequestClassifyRetrieveEngineer decidesDraftReviewIssueRecordPEOPLE KEEP THE DECISIONSAI HANDLES SEARCH, SORTING, DRAFTING
Existing actor or systemAI-supported stepThe same organisation, before and after its workflow is redesigned.

Complexity lives in the connections.

An engineering business is a network of people, processes, information and systems. Each dot on the matrix is an interface where information is handed over and a decision depends on it.

Most of the effort, delay and risk sits on those interfaces, so that is where we look first.

Information exchanged between the twoInterface where AI can reduce effort
01
02
03
04
05
06
07
08
09
10
ClientPEOPLE
01
Engineering
02
Contractor
03
Supplier
04
Design reviewPROCESS
05
Change control
06
Procurement
07
Drawings & modelsINFO
08
Specifications
09
ERP / PLMSYSTEMS
10
FIG. 02 · N² interface matrix for a typical engineering project. Illustrative.

From strategy to a system in operation.

Each capability rests on the one above it. The readiness assessment shows where to start, strategy sets direction, transformation design shapes the workflow, agents and automation do the work, and implementation carries it into daily operations.

Explore Services
START HEREAI Readiness AssessmentWhere AI creates value, which processes suit it, and what to do first.
STRATEGYAI Strategy & ConsultingWhere AI belongs in the business and in what order.
TRANSFORMATION DESIGNBusiness & Process TransformationThe workflow, roles and controls redesigned before anything is automated.
AI SYSTEMAI Agent DevelopmentAgents that read, check and draft in an engineering context.
AI SYSTEMAutomation ServicesRule-based and AI-assisted automation across existing systems.
OPERATIONImplementationIntegration, deployment, adoption and measurement in live operations.
CONNECTS TOERPPLMCAD / BIMMES / QMSDocument controlEmail & portals

Industries we understand from the inside of their workflows.

Explore Industries
Infrastructure project under construction
I.01

AEC / Construction

Owners, designers, engineers, contractors and suppliers work together on each project for a fixed period, each with their own systems. Coordination depends on drawings, models, RFIs, submittals and site reports staying consistent as the project changes.

STAKEHOLDERS
Owner · Architect · Engineers · Contractor · Trades · Authorities
PROJECT INFORMATION
Models · Drawings · RFIs · Submittals · Change orders · Site diaries
  1. A1
    Brief & feasibility
  2. A2
    Design
    ■ Design review checks
  3. A3
    Coordination
    ■ RFI & clash triage
  4. A4
    Procurement
    ■ Bid & submittal review
  5. A5
    Construction
    ■ Site report synthesis
  6. A6
    Handover
    ■ Asset record assembly
I.02

Manufacturing / Engineering

Products move from requirements through design and validation into production and service. Engineering information sits in CAD, PLM, test reports and quality records, and each decision depends on what was decided earlier in the product's life.

Manufacturing: machining cell, assembly line or test bay
RequirementsProduct designDetailed engineeringManufacturingVerification & testValidationQuality & serviceAI · requirements traceabilityAI · design knowledge retrievalAI · test report analysisAI · non-conformance triageDEFINE ↓↑ PROVE
FIG. 06 · Product development as a V: each design decision is checked by a later test. AI connects the two sides.

Research shapes each recommendation.

We study the market a workflow sits in, how AI models behave on the task, and the domain data a solution will depend on. The findings sit underneath the services and shape what we build.

Explore Research
R.01

Strategic Market Research

Understanding markets, industries, businesses and opportunities.
R.02

AI Research

Understanding AI model behaviour and capabilities in specific contexts.
R.03

Domain-Specific AI / ML Research

Exploring AI using domain-specific data and problems.
QUESTION
Where is value concentrated, and how are peers adopting AI?
How does a model perform on this task, and where does it fail?
What does the engineering data contain, and what constraints apply?
INPUTS
Industry reports · operator interviews · adoption patterns
Task samples · model evaluations · failure cases
Drawings · specifications · test and quality data
SUPPORTS
AI StrategyIndustry insight
Agent designModel evaluation
Domain modelsData readiness

Have a workflow worth transforming?

Describe a business, engineering or operational workflow you want to improve. We will start where every engagement starts: understanding how it works today.

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