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RIEMORA

Engineering Intelligent Software.Automating What’s Next.

We build intelligent systems, powerful automation and modern software that help ambitious businesses move forward.

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What Riemora does

Riemora is a software engineering company for AI, automation and custom software. We take a specific problem, a slow process, scattered data or a product that doesn’t exist yet, and engineer software that solves it and keeps working.

  • Founders who need a first product built properly, without a full engineering team.
  • Operations leaders whose teams lose hours to manual steps, re-typed data and scattered documents.
  • Technical teams who need extra capacity for AI, automation or data work alongside their roadmap.

What we build

Five disciplines held to one engineering standard. Start with the one closest to your problem, or describe the problem and we’ll find the right mix.

  • AI Engineering

    Applications built on large language models, retrieval and agents, designed to give answers people can check.

    Put company knowledge and judgement-heavy tasks within reach of software, with guardrails you can inspect.

    AI Engineering services

  • Intelligent Automation

    Workflows that move data between your tools, process documents and remove repetitive manual steps.

    Free people from copy-paste work and make routine processes run the same way every time.

    Intelligent Automation services

  • Custom Software

    Web applications, backends and APIs engineered around how your business actually works.

    Software that fits your process instead of forcing your process to fit an off-the-shelf tool.

    Custom Software services

  • Data Engineering

    Pipelines that collect, clean and shape data so it can be analysed and used by software.

    Turn scattered data into a dependable source for reporting, decisions and AI features.

    Data Engineering services

  • SaaS Product Development

    From first version to production: architecture, accounts, billing and the infrastructure to grow.

    Launch a product on foundations that won't need rewriting once customers arrive.

    SaaS Product Development services

How we engineer

Good software comes from a clear understanding of the problem and steady discipline in how it’s built. These principles shape every engagement.

Understand the problem first
We start with how the work happens today and what it costs, before choosing any technology.
Design around real requirements
Architecture follows the actual constraints: data, users, budget and the people who will maintain it.
Build maintainable systems
Readable code, tests and documentation, so the software outlasts the project that created it.
Measure results
Every system ships with a way to tell whether it works: evaluations, monitoring and the numbers that matter to you.
Improve continuously
Launch is the start. We use what the measurements show to decide what to change next.

Reference architectures

Riemora is a new company, so there’s no client work to publish yet. Here is how we would approach four systems we’re often asked about. They are internal designs, shown to explain our thinking.

  • Knowledge assistant

    Concept design, not a client project

    Problem
    Staff spend time hunting through policies, manuals and past tickets for answers that already exist.
    Approach
    Index approved documents, retrieve the most relevant passages for each question and answer with citations to the source, declining when the documents don't cover it.
    • Document ingestion
    • Hybrid search
    • LLM with citations
    • Evaluation set
    • Access control

  • Workflow automation system

    Concept design, not a client project

    Problem
    Requests arrive by email and forms, then get re-typed into several tools by hand.
    Approach
    Capture each request once, extract the fields, validate them and push them to the right systems, with a review queue for anything uncertain.
    • Intake API
    • Document extraction
    • Rules and routing
    • Human review queue
    • Run monitoring

  • Data intelligence application

    Concept design, not a client project

    Problem
    Numbers live in separate systems, so every report starts with days of manual reconciliation.
    Approach
    Pipe each source into one documented model, check data quality on every load and expose the result through dashboards and a natural-language query layer.
    • Source connectors
    • Transformation models
    • Quality checks
    • Analytics UI
    • Query assistant

  • SaaS foundation

    Concept design, not a client project

    Problem
    A new product needs accounts, billing and tenant isolation before it can take its first customer.
    Approach
    Start from a multi-tenant architecture with authentication, subscription billing, audit logs and monitoring in place, so feature work begins on solid ground.
    • Authentication
    • Tenant isolation
    • Subscription billing
    • Audit logging
    • Observability

From first call to production

Six stages, each with something you can review before the next one starts.

  1. 01

    Discover

    Learn how the work runs today, who it affects and what success should look like.

  2. 02

    Architect

    Choose the approach, data model and technology, and agree a scope for the first release.

  3. 03

    Build

    Develop in short increments you can review, with working software at each step.

  4. 04

    Validate

    Test against real data and real users, including evaluations for any AI component.

  5. 05

    Deploy

    Release to production with monitoring, documentation and a handover to your team.

  6. 06

    Improve

    Track how it performs and refine it based on what the measurements show.

Our own products

Alongside client work, Riemora is developing its own software products. None are public yet.

When a product launches, it will appear here with its status and a link to try it.

See the products page

Have a problem worth solving?

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