LEXIS
Document intelligenceIndexes contracts, tenders and internal policy; cites the exact clause behind every answer.
Input: PDF, DOCX, email → Output: cited answer
80%
Enterprise AI systems
AI systems for organisations.
Rehzen builds products that automate document, support and operations workflows with AI. We build and run our own products, then apply the same infrastructure to client work.
4Products in development
12Projects delivered
6–10weeksTypical delivery time
48hoursFirst response time
Products
Products we build ourselves
Four products on one shared infrastructure. Each one targets a single operational need.
Beta
ECHO
Support agentClassifies requests, drafts replies, opens the CRM record and routes the result for approval.
Input: email, live chat → Output: approved reply
55%FORGE
Catalogue generationTurns product images and spec sheets into multilingual catalogue copy.
Input: image, PDF → Output: catalogue content
35%ARGUS
Process observerWatches workflow events, catches drift and delay early, produces a weekly report.
Input: event stream → Output: anomaly and report
20%Progress reflects internal milestones; release dates are targets.
Architecture
The life of a request
Every request follows the same path: context, model, tools, answer.
01Input
02Context
03Model and tools
04Answer
Services
End-to-end system delivery
Every AI step under one contract: decision, design, build, operation.
Strategy and discovery
We decide together which processes to automate, what data is needed and how success is measured.
System design
Model, data pipeline, tools and interface — architecture designed around your reality.
Integration
Connected to your ERP, CRM and document systems. Data stays in place, access stays scoped.
Operation and improvement
After go-live, monitoring, cost control and continuous improvement stay with us.
Capabilities
Parts of the system
Not one product — the parts we assemble for the job.
- Document search (RAG)
- Agents
- OCR and parsing
- Speech and transcripts
- Process automation
- Evaluation sets
- Guardrails
- Observability
Process
Four stages, written output
Every stage ends with a document and a decision. No surprises.
- 011–2 weeks
Discovery
Processes, data sources, constraints. Output: scope note.
- 022–3 weeks
Design
Architecture, model selection, success metrics. Output: technical design.
- 033–5 weeks
Pilot
A vertical slice running on real data. Output: measurement report.
- 04ongoing
Go-live
Rollout, training, handover. Output: operations documentation.
FAQ
Common questions
Do you use your own model?
No. We do not train models. We select the right model for your case and build the rest of the system.
Does our data leave the country?
By default, no. We offer cloud, private cloud and on-premise deployments.
How long does a build take?
A typical deployment takes 6–10 weeks; the pilot runs within the first 3–5 weeks.
What happens after go-live?
Monitoring, cost control and improvement stay with us. The system is yours; operations are ours.
What does AI consulting cover?
Process analysis, feasibility, model and architecture selection, integration planning and go-live. Output: a written scope and roadmap.
What is needed for an LLM integration?
Access to your data sources, one process chosen for the pilot, and a decision maker. Model, orchestration and interface are ours.
Team
Two cities, one team
Five hours between Istanbul and Guangzhou means a working rhythm that spans the whole day.
IstanbulGMT+3
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Headquarters
41.0082° N · 28.9784° E
GuangzhouGMT+8
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Operations
23.1291° N · 113.2644° E