Empowering Your Toughest Engineering Challenges
with Rapid-Prototype, Ethical AI Solutions
At Robinson Engineering, we empower organisations to solve their toughest engineering challenges by rapidly prototyping then deploying pragmatic AI solutions that deliver real ROI. Importantly, we do it all in a people-first culture that balances relentless curiosity with true work-life harmony.
GATEWAY FREE AI ASSESSMENT SERVICE
Our gateway service provides a no-cost, 60-minute session where we guide you through a concise assessment of your organisation’s AI maturity. You’ll walk away with a clear report of your strengths, a high-impact pilot idea, and a “gap alert” highlighting the blockers most likely to stall your progress.
Spend xx minutes completing our online survey, providing us with the information we need to produce the free insights. We then analyse the information and deliver a 60 minute reveal session which is followed up by a full report into your AI maturity, the critical "gotchas" that can be overlooked and a pilot concept that will drive quick ROI.
Pre-call questionnaire
60 minute live walk through
Report delivery
Immediate value
SERVICES
Moving on from our gateway service we offer a comprehensive suite of AI services to meet any business or team exactly where they are
AI READINESS ASSESSMENT SERVICE
Build the foundations for AI success quickly, confidently and with a clear path forward. Is your organisation poised to turn data into decisions? Our AI Readiness Assessment delivers a comprehensive health check across the four pillars every AI initiative needs: Data Foundations, Technology Stack, People & Skills, and Governance & Ethics. In just XXX weeks, you’ll receive a tailored roadmap that sequences quick-win pilots and strategic capability builds, so you can move from proof-of-concept to production at pace.
AI POLICY DEVELOPMENT SERVICE
Navigating data privacy regulations, bias mitigation or model explainability doesn’t have to slow you down. Our AI Policy Development Service delivers a tailored set of policies, playbooks and training materials, so your teams can accelerate AI projects without risking compliance or reputational damage.
END TO END AI CONSULTANCY SERVICE
From strategy to production, we guide you every step, delivering real AI impact at scale. Turn High-Value AI Ideas into Production-Ready Solutions. Stop letting pilots stall and promise fade. Our full-service AI Consulting engagement combines strategic advisory, rapid prototyping, MLOps engineering, and team upskilling, so your organisation moves from concept to scalable deployment in weeks, not months.
CASE STUDY: How RE Saved 80% on law firm costs & cut report delivery time from 7 days to 1 minute
Overview
A leading international law firm engaged Robinson Engineering (RE) to streamline their real-estate planning condition due diligence process. Traditionally a manual, time (and cost) intensive task, this engagement leveraged large language models (LLMs) to automate classification and reporting, dramatically reducing turnaround times and increasing accuracy.
The Problem
Lawyers were spending a week or more manually reviewing development planning conditions, billing between £5,000–£10,000 per report. Due to the manual element there was always a risk of human error as these documents are typically complex and verbose leading to occasional misclassifications or omissions, exposing clients to compliance risks and project delays. For this particular revenue stream it was very difficult to scale as growing transaction volumes meant the firm could not scale this service profitably without significant headcount increases.
The Approach
RE collaborated with the firm’s planning-condition specialists to define six client-specific condition types (e.g., environmental, infrastructure, community-impact). We chose an open-source large language model, then fine-tuned it on a curated dataset of historical planning reports, annotated by the firm’s experts.
We then built a lightweight processing pipeline to:
- Ingest planning condition text
- Classify each item into one of the six types
- Generate draft summaries conforming to the firm’s existing report template
We wanted to incorporate a "human in the loop" validation system so we deployed an initial review interface allowing senior associates to spot-check and correct any edge-case misclassifications, feeding those corrections back to further refine the model.
The Final Solution
- Processes any planning-condition document in under 60 seconds, tagging each clause with its condition type.
- Automatically populates the firm’s standard due-diligence report format, including executive summary, condition tables, and recommended actions.
- Provides a simple web UI showing model confidence scores and flagged items for optional human review.
Outcomes
- Dramatic cost reduction: The delivered reports are now produced at a fraction of the original cost with 80% savings compared to manual billing
- Turnaround times shrank from 1+ week to under 1 minute, allowing the firm to offer express services.
- Improved accuracy: The LLM outperformed human reviewers in detecting and classifying conditions, catching several misclassifications or omissions that had previously slipped through.
- Scalability: The firm can now handle unlimited volumes without proportional headcount increases, opening new revenue opportunities in high-volume property markets.
This engagement demonstrates how targeted AI prototyping, when paired with domain expertise, can transform a costly, error-prone legal process into a fast, accurate, and scalable service offering.
CASE STUDY - How RE boosted digitisation accuracy by 30% & reduced processing time from days to minutes
Overview
An international Oil & Gas operator needed to extract structured data from imperfect, large-format well-log scans. Robinson Engineering delivered an AI-driven pipeline that automates segmentation and digitisation—transforming days-long manual workflows into minute-scale, high-accuracy processes.
The Problem
Well logs combined free text, tables, and plotted graphs, often as low-quality manual scans. Because the formats were complex and mixed, Geoscientists spent several days per log, manually tracing curves and transcribing values. It was time consuming and manual. Results varied widely depending on the individual analyst’s skill and fatigue, introducing data gaps and errors and consistency was an issue. Because of the nature of the foundational set up, only the highest-priority logs were digitised, leaving large geographic areas unanalysed.
The Approach
RE partnered with the client to gather a representative set of scanned well-log images and establish the industry standard output format. We then trained a convolutional neural network to identify and separate text blocks, tables and graph regions in each scan. The custom vision pipeline we subsequently developed was able to:
- Convert segmented graph regions to high-contrast formats
- Trace individual log curves (e.g., porosity, resistivity) using edge-detection and spline-fitting techniques
To help the Geoscientists interact with the system we built a user-friendly web interface allowing them to upload scans, this then triggered the segmentation and extraction pipeline, and exported the results in the client’s standard Well Log Digital Exchange (WLDE) format.
The Final Solution
- Processes each well log scan in under 5 minutes, isolating and digitising all curves and tabular entries.
- Generates WLDE-compliant files ready for downstream reservoir-modelling tools.
- Offers a lightweight web app where geoscientists upload scans, monitor progress and download results, no coding or manual tracing required.
Outcomes
- Reduced log digitisation from several days to minutes, enabling batch processing of hundreds of logs overnight.
- Achieved an order-of-magnitude reduction in per-log processing costs, making it economical to digitise entire well fields.
- Model accuracy exceeded individual human analysts and curve tracing errors dropped by over 30%, whilst consistency between logs improved by 50%.
- Client now digitises full well-log inventories across large geographies, unlocking new insights in reservoir characterisation that were previously cost-prohibitive.
By combining advanced computer-vision models with domain-specific extraction logic, this solution turned a labour-intensive bottleneck into a rapid, reliable and scalable service essentially reshaping how well-log data is consumed across the organisation.
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