Enquiries become manual projects
Before
People interpret emails, search product data and assemble quotes by hand.
With a connected AI workflow
Requirements are structured, drafts prepared and exceptions routed for review.
Practical AI solutions · Stockholm
We turn complex work into intelligent systems.
Cortiv Labs designs and builds practical AI solutions that connect your data, tools and teams, reducing manual work and creating more room to grow.
AI automation · software engineering · systems integration
Illustrative intelligent workflow
The opportunity
The expensive work is often hiding in plain sight.
AI is most useful when it removes friction from a real operation, not when it is added without a measurable reason.
Operations live between systems
Before
Teams copy information across inboxes, documents, CRM, ERP and spreadsheets.
With a connected AI workflow
A governed workflow coordinates approved data and actions across existing tools.
Customer questions interrupt the team
Before
Routine order and policy questions require several lookups and repeated replies.
With a connected AI workflow
Context is retrieved, responses drafted and unusual cases escalated to a person.
Solutions
Practical solutions for work that slows the business down.
Each engagement begins with a workflow and a business outcome. The technology follows from what the operation actually needs.
01 · Emerging opportunity
AI commerce infrastructure
Explore how structured product data, governed APIs and Universal Commerce Protocol concepts could make your catalogue understandable and actionable across AI-assisted buying journeys.
Exploratory concept, validated through discovery and a focused technical pilot.Explore this solutionConceptual illustration
02 · Revenue operations
AI sales & quotation automation
Turn incoming enquiries into structured requirements, grounded quotation drafts and organised follow-ups, with people retaining commercial approval.
Illustrative solution pattern. Scope and value are validated with your real quotation process.Explore this solutionConceptual illustration
03 · Operational efficiency
AI business process automation
Reduce repetitive document, data-entry and coordination work while preserving auditability, business rules and human control.
Illustrative solution pattern, designed around your controls, data and operating environment.Explore this solutionConceptual illustration
04 · Customer operations
AI e-commerce operations assistant
Give operations teams faster access to order context, policies and next actions while routing exceptions and sensitive decisions to people.
Illustrative assistant concept, not an off-the-shelf product or deployed customer claim.Explore this solutionConceptual illustration
What we could build
See the workflow change, not just the model.
These are illustrative workflows, not existing products or customer case studies. A pilot would adapt and evaluate them against your real operation.
Conceptual example
Operational problem
Slow response to quote requests
- 01Enquiry received
- 02Requirements extracted
- 03Data checked
- 04Draft prepared
- 05Human approval
Common pilot measuresResponse and cycle timeManual touches per caseError and rework rateWork completed per employeeEscalation and exception rateCustomer response consistency
The intelligence layer
One connected workflow, from signal to measured action.
Useful AI is more than a chat window. It understands the request, retrieves trusted context, works within business rules and keeps people in control.
- 01
Understand
Capture an email, document, request or event and determine what it means.
- 02
Retrieve
Find the approved data, policy, history and context needed for the task.
- 03
Decide
Apply business rules and AI reasoning within defined permissions and thresholds.
- 04
Act
Prepare a response, update a system or route the next action to the right person.
- 05
Learn
Measure quality, exceptions, time and cost so the workflow improves responsibly.
Specialist capability
Custom AI & LLM engineering
For technical teams whose challenge does not fit a standard pattern, we design and build tailored RAG, intelligent search, model integrations, AI applications and production infrastructure.
Explore engineering capabilities- RAG and intelligent search
- LLM and API integration
- Evaluation and guardrails
- Model deployment and observability
- Data engineering and cloud infrastructure
- Custom applications and internal tools
Fits your operation
Keep the systems that already run your business.
We connect the workflow across approved tools, data and APIs. The AI layer helps interpret and coordinate work; your operational systems remain the source of truth.
Cortiv-designedAI workflowPermissions · logic · review
- Email and shared inboxes
- CRM and sales platforms
- ERP and order systems
- E-commerce and help desks
- Accounting and document tools
- Data platforms and internal APIs
Illustrative integration map
How we work
Discover first. Prove value before scaling.
The goal is not to sell a predetermined product. It is to identify a worthwhile operational problem and find the smallest responsible way to improve it.
- 01
Discover
Map the workflow, people, systems, risk and commercial outcome.
Prioritised opportunity - 02
Design
Define a focused assisted workflow, human controls and success measures.
Pilot architecture - 03
Pilot
Test with representative work and evaluate quality, effort, cost and exceptions.
Evidence for a decision - 04
Implement
Integrate the proven workflow, monitoring and operational documentation.
Operational capability
Responsible by design
Automation where it helps. Human judgement where it matters.
Control is part of the system architecture, not an afterthought.
Governed access
Connect only approved data and actions, with permissions designed for the workflow.
Human oversight
Keep people responsible for sensitive, unusual or commercially important decisions.
Observable quality
Evaluate outputs, record exceptions and monitor the measures that determine whether the system is useful.
Where we focus
Built around the operation, not an industry buzzword.
We start with the repeated work, systems and commercial constraint. These are practical starting points for the organisations we are speaking with.
Wholesale & manufacturing
- Complex quotation preparation
- Product and availability lookup
- Order exception coordination
- Document and data-entry automation
E-commerce & retail
- Order and delivery enquiries
- Returns triage
- Customer-service assistance
- Catalogue and commerce infrastructure
Professional services
- Document intake and classification
- Client information retrieval
- Drafting and review workflows
- Administrative automation
Technology teams
- RAG and intelligent search
- AI features in existing products
- Model and API integration
- Production AI infrastructure
Why Cortiv Labs
Technical depth, applied to a business decision.
No invented customer logos or inflated promises. Just the capabilities and working principles we can stand behind.
Based in Stockholm, Sweden
Cortiv Labs supports organisations in Sweden and internationally.
Full-system engineering
Capabilities span software, AI and LLM integration, RAG, APIs, automation, data engineering and cloud infrastructure.
Evidence before expansion
A focused pilot can test quality, operational fit and economics before a broader implementation decision.
Human control by design
Permissions, source controls, approvals, evaluation and fallback behaviour are designed for the risk of the workflow.
Decision tools
Make the next AI decision with better evidence.
Practical tools for finding the right workflow, testing the business case and planning a dependable system.
Assessment01
AI opportunity assessment
Score a workflow across value, repetition, data readiness, risk and adoption to find the strongest place to start.
Assess an opportunityCalculator02
AI automation ROI calculator
Model the hours and operating cost a well-scoped automation could recover each year.
Estimate the valueGuide03
How to plan an AI project
A practical framework for moving from a promising workflow to a testable, governed production system.
Read the guideFrequently asked
A practical first step into AI.
Where should a company start with AI automation?
Start with a frequent workflow that consumes meaningful time, has accessible information and produces an outcome you can measure. Discovery should confirm whether AI is appropriate before a build begins.
Do we need to replace our current systems?
Usually not. We design around the tools and data you already use, then add the smallest reliable integration and AI layer needed to improve the workflow.
What happens during a discovery call?
We discuss the workflow, who performs it, where work gets delayed, which systems are involved and what a valuable improvement would look like. It is a working conversation, not a commitment to build.
Can you begin with a pilot?
Yes. A focused pilot is often the safest way to evaluate quality, adoption, operating cost and business value before a larger implementation.
How do you manage AI risk?
The design can include permissions, source controls, human approvals, evaluation, monitoring and clear fallback behaviour according to the workflow and its risk.
Is AI commerce infrastructure already a Cortiv Labs product?
No. It is an emerging solution area we can explore and validate with commerce organisations. Any interface shown is conceptual and does not represent an existing deployed product.
Start with the workflow
Show us where the work gets stuck.
Tell us about the repeated task, the people involved and the systems it touches. We’ll use the conversation to assess whether there is a valuable, responsible place to apply AI.
Prefer email?hello@cortivlabs.com