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Services

Custom software. Applied intelligence. Experimental engineering.

KRATT works across software engineering, applied AI and technical research, backed by senior technology advisory. Engagements can be scoped as one-off projects, retained support, fractional leadership or research assignments.

01 / 05

Custom Software & Integrations

Custom software built around the way your business actually works, from internal tools and integrations to production platforms.

Typical problems

  • Critical work held together by spreadsheets, re-keying and manual exports.
  • Systems that do not talk to each other, so data is duplicated or wrong.
  • A product idea that needs a reliable first production version.
  • Reporting that takes days to assemble by hand.

Capabilities

  • Web applications
  • Internal business systems
  • APIs and integrations
  • Data workflows
  • Mobile solutions
  • Reporting and automation
  • Architecture and production deployment

Typical engagement outputs

  • Agreed scope, architecture and delivery plan
  • Working software delivered in reviewed increments
  • Source code, infrastructure configuration and documentation handed over
  • Deployment, monitoring and support arrangements
02 / 05

AI Archaeology

Understand the software your business already runs, then rebuild it properly. We use today's AI to excavate legacy systems and turn what we find into a modern, scalable solution fitted to how you work now.

Typical problems

  • A business-critical system whose original developers are long gone, with little or no documentation.
  • Business rules that exist only in old code, stored procedures or spreadsheets, and nobody can say exactly what they are.
  • A platform that is expensive to change, hard to host securely and cannot scale with the business.
  • Several overlapping systems built over the years that should really be one.

Capabilities

  • AI-assisted code and database analysis
  • Reverse-engineering of business rules and data flows
  • Architecture and dependency mapping
  • Technical debt and risk assessment
  • Documentation of existing systems
  • Target architecture and modernisation roadmap
  • Staged migration and data migration
  • Rebuilding on current, supported technology
  • Parallel running and behaviour verification against the old system

Typical engagement outputs

  • A written map of the existing system: components, data, integrations and embedded business rules
  • Assessment of what to keep, replace or retire, with risks and effort
  • Target architecture and a staged modernisation plan
  • The new system, delivered in increments and verified against the old one
  • Documentation your team can maintain
03 / 05

AI, Automation & Computer Vision

Applied AI and computer vision for problems where ordinary software rules are not enough.

Typical problems

  • Repetitive document or email handling that consumes skilled staff time.
  • Visual inspection or counting done manually from photos or video.
  • Measurements that need to be taken from images rather than by hand.
  • An AI pilot that looked promising but was never evaluated or productionised.

Capabilities

  • AI-assisted workflows
  • LLM integrations
  • Process automation
  • Machine learning
  • Image analysis
  • Object detection
  • Segmentation
  • Image-based measurement systems
  • Model evaluation

Typical engagement outputs

  • Problem framing with measurable success criteria
  • Evaluation dataset and documented test results
  • Working model or AI workflow integrated into your systems
  • Monitoring and retraining approach for ongoing operation
04 / 05

Research & Experimental Development

Structured investigation where the technical answer is not known in advance: define the uncertainty, test candidate approaches and document what works.

Typical problems

  • A concept that depends on a technical capability nobody has proven yet.
  • Accuracy or performance requirements that existing methods do not meet.
  • Several possible approaches and no evidence about which will work.
  • A need for documented technical evidence before committing investment.

Capabilities

  • Technical feasibility studies
  • Systematic investigation of technical uncertainty
  • Proof-of-concept development
  • Experimental software
  • Measurement and validation systems
  • Prototype evaluation
  • Technical research reporting

Typical engagement outputs

  • Defined objective and statement of technical uncertainty
  • Experiment plan with evaluation criteria
  • Prototypes and recorded experimental results
  • Technical report with conclusions and recommended next steps
05 / 05

Technology Advisory

Senior technical judgement for technology decisions, architecture, vendors, delivery and risk.

Typical problems

  • A major technology decision or vendor selection without an internal expert.
  • An engineering team that needs senior leadership but not a full-time CTO.
  • An investment or acquisition that depends on software nobody has reviewed.
  • A delivery programme that is late, over budget or unclear.

Capabilities

  • Fractional CTO support
  • Architecture reviews
  • IT strategy
  • Vendor assessment
  • Software and product due diligence
  • Delivery planning
  • Technical risk assessment
  • Security and operational reviews

Typical engagement outputs

  • Written findings with prioritised recommendations
  • Architecture or vendor decision records
  • Delivery or remediation plan
  • Ongoing technical leadership on an agreed cadence

Engagement models

Scoped to the problem, not to a package.

Pricing depends on scope and is agreed in writing before work starts.

  • A

    Project delivery

    A defined outcome, scope and timeline - for example an identity rollout, an integration or a new internal system.

  • B

    Retained engineering support

    Ongoing development, maintenance and support of software we have built or taken over, with an agreed scope and cadence.

  • C

    Fractional technology leadership

    Senior technical leadership for a set number of days per month, without a full-time executive hire.

  • D

    Research / feasibility engagement

    A time-boxed investigation of a technically uncertain problem, ending in documented results and a recommendation.

Have a technology problem that needs ownership?

Tell us what is not working, what you are trying to build or what you need to understand.

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