Services
Intelligence built into your business.
Eleven disciplines, one engineering practice. Each service below starts from a business challenge and ends with a system that runs in production.
AI Automation
Transform repetitive business processes into intelligent automated workflows.
- Business challenge
- Teams spend hours re-keying data between inboxes, documents and systems. Rule-based automation breaks the moment an input looks slightly different.
- CLEEV solution
- We design workflows where AI handles the unstructured parts — reading, classifying, extracting — and deterministic automation handles the rest, with validation and human approval where it matters.
Capabilities
- Business process automation
- Intelligent workflows
- n8n automation
- Document automation
- CRM / ERP workflows
- Operational automation
Possible use cases
- Inbound email triage and routing
- Invoice and order document processing
- Lead qualification and CRM enrichment
- Back-office reconciliation and reporting
How it works
01
Map
Document the process as it actually runs, including the exceptions.
02
Design
Decide where AI adds judgement and where rules guarantee correctness.
03
Automate
Build the workflow with logging, retries and human-in-the-loop steps.
04
Measure
Track throughput, exception rates and quality, then iterate.
AI Integration
Integrate advanced AI capabilities into existing applications, platforms and business systems.
- Business challenge
- Most organisations do not need another standalone tool. They need AI inside the systems their people already use, connected to the data those systems hold.
- CLEEV solution
- We integrate large language models and AI services into your applications and platforms through clean, observable APIs — model-agnostic, so you are never locked to a single provider.
Capabilities
- OpenAI
- Claude
- Gemini
- Open-source LLMs
- API integration
- ERP / CRM integration
Possible use cases
- AI features inside an existing product
- Summaries and drafting inside CRM or ticketing
- Classification and extraction services for internal systems
- Model routing across providers by cost and quality
How it works
01
Assess
Review the target systems, data flows and constraints.
02
Architect
Define an integration layer with evaluation, fallbacks and cost controls.
03
Integrate
Ship AI capabilities behind stable, versioned interfaces.
04
Operate
Monitor quality, latency and spend in production.
AI Agents.
Build intelligent assistants capable of helping customers, employees and business operations.
- Business challenge
- Chatbots that only answer questions rarely change outcomes. Useful agents need to take actions — safely, with the right permissions and a clear audit trail.
- CLEEV solution
- We build agents that reason over your knowledge, call your tools and complete multi-step tasks, with guardrails, approval steps and full observability.
Capabilities
- Customer agents
- Internal assistants
- Voice AI
- Sales assistants
- Research agents
- Multi-agent workflows
Possible use cases
- Customer service agents that resolve, not just respond
- Internal assistants connected to policies and systems
- Sales assistants that prepare account briefs
- Research agents that compile sourced reports
How it works
01
Scope
Define the tasks, tools and boundaries the agent is allowed to use.
02
Ground
Connect knowledge and systems with permission-aware access.
03
Guard
Add approvals, limits and evaluation before anything reaches users.
04
Observe
Trace every step so behaviour is explainable and improvable.
Custom AI Solutions
Develop tailored artificial intelligence platforms around specific business requirements.
- Business challenge
- Off-the-shelf AI products fit generic problems. Competitive advantage usually sits in processes and data that are specific to your organisation.
- CLEEV solution
- We design and engineer AI systems around your requirements — from retrieval and document intelligence to recommendation engines and full AI-native applications.
Capabilities
- AI SaaS
- Enterprise AI applications
- RAG systems
- Document intelligence
- Semantic search
- Recommendation systems
Possible use cases
- Domain-specific AI applications for internal teams
- AI-native SaaS products
- Document understanding pipelines
- Personalisation and recommendation engines
How it works
01
Define
Translate a business goal into measurable AI requirements.
02
Prototype
Validate feasibility on real data before committing to scale.
03
Engineer
Build the production system: data pipelines, models, application.
04
Evolve
Improve with feedback loops and evaluation datasets.
RAG & Knowledge Systems
Turn documents, databases and internal know-how into answers your teams can trust.
- Business challenge
- Critical knowledge is spread across file shares, wikis, tickets and databases. People spend too long searching — and generic AI tools cannot see any of it.
- CLEEV solution
- We build retrieval-augmented systems that search your sources, respect existing permissions and cite where every answer came from.
Capabilities
- Retrieval-augmented generation
- Semantic & hybrid search
- Vector databases
- Knowledge graphs
- Source citations
- Access-controlled retrieval
Possible use cases
- Policy and procedure assistants
- Technical documentation search
- Contract and case-file research
- Support knowledge for service teams
How it works
01
Connect
Ingest sources with their structure and access rights intact.
02
Index
Chunk, embed and link content for precise retrieval.
03
Answer
Generate responses grounded only in retrieved, permitted sources.
04
Evaluate
Measure answer quality against curated test questions.
Generative AI.
Put content generation to work inside controlled, brand-safe business processes.
- Business challenge
- Generative AI can draft, translate and summarise at scale — but unmanaged use creates inconsistent quality, brand risk and data exposure.
- CLEEV solution
- We build generative workflows with templates, review steps and evaluation, so output is consistent, on-brand and appropriate for its audience.
Capabilities
- Document drafting
- Summarisation
- Translation & localisation
- Structured content generation
- Prompt & template systems
- Output evaluation
Possible use cases
- Proposal and report first drafts
- Multilingual content for DE / FR / IT / EN markets
- Meeting and case summaries
- Product descriptions from structured data
How it works
01
Template
Capture tone, structure and rules as reusable templates.
02
Generate
Produce drafts from approved inputs only.
03
Review
Route output through human review where required.
04
Improve
Use edits as feedback to raise first-draft quality.
Software Engineering
Build scalable applications and digital platforms engineered for long-term business use.
- Business challenge
- AI features are only as reliable as the software around them. Fragile codebases and ad-hoc infrastructure make every new capability slower and riskier.
- CLEEV solution
- We engineer modern web applications, SaaS platforms, APIs and backends with typed code, automated testing and infrastructure designed to be operated for years.
Capabilities
- Web applications
- SaaS platforms
- Backend development
- APIs
- Enterprise systems
- Cloud applications
Possible use cases
- Customer portals and internal tools
- Multi-tenant SaaS platforms
- API backends for mobile and web
- Modernising legacy applications
How it works
01
Architect
Choose a stack and structure that fit the product's lifespan.
02
Build
Deliver in short iterations with reviews and automated tests.
03
Ship
Deploy through CI/CD pipelines with monitoring from day one.
04
Maintain
Keep dependencies, security and performance in good order.
Data & AI Engineering
Build the pipelines, models and data foundations that AI systems depend on.
- Business challenge
- AI projects stall when data is inconsistent, inaccessible or undocumented. Models need clean, governed, well-structured inputs.
- CLEEV solution
- We design data pipelines, storage and quality controls so that analytics and AI systems can rely on the same trusted foundation.
Capabilities
- Data pipelines (ETL / ELT)
- Data modelling
- PostgreSQL & warehouses
- Embedding pipelines
- Data quality checks
- MLOps foundations
Possible use cases
- Consolidating data from operational systems
- Preparing document corpora for retrieval
- Feature pipelines for prediction models
- Monitoring data freshness and quality
How it works
01
Inventory
Map sources, owners and quality issues.
02
Model
Design schemas that reflect how the business works.
03
Pipeline
Automate movement and transformation with tests.
04
Govern
Document lineage, access and retention.
AI Strategy & Transformation.
Identify high-value AI opportunities and create a practical path from concept to deployment.
- Business challenge
- Many organisations have dozens of AI ideas and no clear way to decide which ones are worth building, in which order, and on what architecture.
- CLEEV solution
- We assess readiness, prioritise use cases by value and feasibility, and turn the result into a roadmap with architecture and proofs of concept — not a slide deck that sits on a shelf.
Capabilities
- AI readiness
- Use-case discovery
- AI roadmap
- Architecture
- Proofs of concept
- Transformation strategy
Possible use cases
- Executive AI opportunity workshops
- Use-case portfolio prioritisation
- Target architecture for AI platforms
- Proof of concept before investment decisions
How it works
01
Discover
Interview teams and map processes, data and pain points.
02
Prioritise
Score use cases by value, feasibility and risk.
03
Plan
Define architecture, sequencing and ownership.
04
Prove
Validate the highest-value idea with a working proof of concept.
AI Governance
Put security, privacy and human oversight into how AI is built and operated.
- Business challenge
- As AI moves into core processes, leadership needs to know which systems exist, what data they use, how they are monitored and who is accountable.
- CLEEV solution
- We help define practical governance — policies, access models, evaluation and monitoring — and build those controls directly into the systems we deliver.
Capabilities
- AI usage policies
- Risk assessment
- Access control design
- Human-in-the-loop design
- Evaluation & monitoring
- Audit logging
Possible use cases
- Inventory of AI systems and data flows
- Approval workflows for high-impact actions
- Monitoring dashboards for AI quality
- Guidelines for employee use of AI tools
How it works
01
Inventory
Identify AI systems, data and decision points.
02
Assess
Evaluate risks and required controls for each use.
03
Implement
Build controls into systems, not just documents.
04
Monitor
Review performance and incidents continuously.
API & System Integration
Connect platforms, applications and data so information flows where it is needed.
- Business challenge
- Disconnected systems create duplicate entry, inconsistent data and processes that depend on people copying information by hand.
- CLEEV solution
- We design and build integrations — APIs, webhooks and event-driven flows — that connect CRM, ERP, databases and custom applications reliably.
Capabilities
- REST & GraphQL APIs
- Webhooks & events
- ERP / CRM connectors
- Middleware & orchestration
- Authentication & security
- Integration monitoring
Possible use cases
- Synchronising CRM and ERP records
- Exposing legacy systems through modern APIs
- Event-driven notifications across tools
- Partner and supplier data exchange
How it works
01
Map
Identify systems of record and the flows between them.
02
Contract
Define interfaces, schemas and error handling.
03
Connect
Build integrations with retries, idempotency and logging.
04
Watch
Monitor failures and data drift across systems.
Start a conversation
Not sure which service fits?
Describe the problem. We will tell you honestly which approach — if any — makes sense.