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DIGITAL PLACE — ENGINEERING COMPANY

Expertise

One architectural landscape: information systems, software, data, automation and AI combine according to the problem.

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Clarity · Rigour · Results

Expertise register

Engineering continuity.

From business context and decisions through to production: understand, architect, build, secure, industrialize and evolve without artificially separating information systems, software, data, automation and AI.

  1. Information systems & Software Engineering

    Designing and evolving coherent, integrated, secure and maintainable systems, treating Software Engineering as a discipline of architecture, quality and production, beyond code generation.

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    Capabilities

    • Application and technical architecture
    • APIs and integration
    • Web/mobile applications
    • Domain design
    • Microservices where appropriate
    • IAM
    • Migration/modernisation
    • Performance/high availability
    • CI/CD
    • Observability
    • Production Readiness

  2. Data, decision support & Machine Learning

    Turning heterogeneous data into reliable information, explainable models and usable decisions, starting with the decision to inform or automate where appropriate.

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    Capabilities

    • ETL/ELT
    • Lakehouse
    • Reference datasets
    • Quality
    • Lineage
    • BI
    • Decision Engineering
    • NLP
    • Scoring
    • Forecasting
    • Optimisation
    • MLOps
    • Model APIs
    • Performance and drift monitoring

  3. Workflow & Automation Engineering

    Redesigning the workflow before automating it, then orchestrating people, software, data and agents with the requirements of a production system.

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    Capabilities

    • Workflow & Decision Redesign
    • Mapping and Process Intelligence/Mining where logs allow it
    • Decision Contracts
    • Human × Software × Agent allocation
    • Integrations/APIs
    • Rules
    • Human-in-the-loop
    • Exception design
    • Runtime
    • Retries/idempotency
    • Observability
    • Workflow registry and governance

  4. Generative AI & agentic systems

    Integrating AI and agents into information systems with explicit rules for data, context, identities, tools, permissions, Runtime, testing, control and observability.

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    Capabilities

    • RAG
    • Context Engineering
    • Multilingual assistants
    • Agents
    • Orchestration
    • MCP
    • Tool calling
    • Agent identity
    • Runtime
    • Model gateway/routing/fallback
    • Evaluation
    • Verification
    • Security
    • Audit
    • Observability
    • LLMOps
    • Serving
    • French/Arabic/Darija depending on the use case

  5. Document Intelligence, Computer Vision & voice

    Extracting, understanding and using documents, images and voice in integrated processing pipelines.

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    Capabilities

    • French/Arabic OCR
    • Detection/rectification
    • MRZ
    • Computer Vision
    • STT/TTS
    • NLP
    • API integration
    • Results QA

OUR ENGINEERING

Designing what must remain under control.

Code, rules, Data or AI: technical choices serve the system’s needs.

Discover our approach

Problem first

Decisions, processes, users, data, constraints and responsibilities before tools.

Production by design

Security, performance, availability, scalability, CI/CD, observability, rebuilding and maintainability shape the architecture from the outset.

Evidence before promise

Tests, metrics, traces, acceptance criteria, Evaluation, Verification and regression testing provide evidence of quality.

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LET’S TALK

Let’s discuss your challenge.

A system to build or evolve?

Discuss your system