NHS-Compliant Prescription Infrastructure
An optometry group operating under NHS contract faced critical inefficiencies in its prescription process — paper-based workflows, inconsistent clinical practices, and regulatory exposure. The system lacked audit trails, dosage controls, and integration with existing PMS tools.
We were brought in to redesign the prescription lifecycle from the ground up. The outcome was OptiScribe — a regulatory-grade SaaS platform built to streamline prescribing, reduce risk, and meet NHS documentation standards.
Audited the full prescription workflow across multiple clinics and clinicians.
Identified regulatory gaps, clinical friction points, and data handling failures.
Co-developed a compliant, streamlined operating model ready for digital execution.
Delivered a bespoke SaaS platform built around NHS FP10 requirements.
Integrated with OPTIX via secure API for real-time patient data access.
Engineered structured drug database, dosage safety logic, and print-and-sign workflows.
Created the OptiScribe brand identity, naming system, and visual direction.
Designed the clinical UI/UX interface to meet NHS accessibility and usability standards.
Produced the product website, explainer assets, and onboarding experience.
Multi-Site Clinical Operations and Brand Transformation
CES Medical — a provider operating three NHS-contracted ophthalmology clinics — faced operational fragmentation, brand inconsistency, and limited visibility across its locations. Systems were decentralised, internal governance was undocumented, and the business lacked a scalable foundation for growth or exit.
We partnered with the executive team to stabilise operations, create internal infrastructure, and reposition the company under a unified identity. The result was a full-stack transformation — from workflows and data systems to brand and board governance.
Conducted an end-to-end operational audit across all three clinical sites.
Developed standardised internal governance models, SOPs, and audit documentation.
Advised management on the operational setup required to scale to 20 clinics nationally.
Designed an exit-aligned growth roadmap to support long-term PE acquisition.
Structured and deployed a centralised SharePoint-based knowledge system.
Built custom document workflows and compliance file repositories.
Designed dashboards for task management, reporting, and clinic-wide oversight.
Advised and led the rebranding of the organisation into CES Medical, consolidating all sites.
Developed a modern visual identity, tone of voice, and digital design language.
Built the flagship website, including clinic pages, referral flows, and service structure.
Customer Claim Management Infrastructure
Athena is a behavioural intelligence module designed to manage customer claims with speed, accuracy, and fraud resilience. Built within the Alyssa platform, it integrates seamlessly into retail workflows to detect anomalies, validate legitimacy, and optimise operational response — protecting both margin and customer trust.
Partnered with operations and CX leadership to map the full customer claim lifecycle.
Identified failure points in existing claim resolution logic, manual triage inefficiencies, and fraud vulnerability.
Designed a rule-based intervention framework to prioritise legitimate claims while flagging outliers in real-time.
Delivered Athena as a fully embedded module for E-Sentinel.
Combined behavioural analytics, delivery data, and fraud patterns to generate confidence-scored claim recommendations.
Integrated with CRM, logistics, and returns systems to ensure automation without process disruption.
Designed the Athena UI as an intuitive claims dashboard, allowing teams to filter, review, and act with minimal input.
Built a visual scoring model and recommendation interface optimised for speed and decision clarity.
Created stakeholder messaging and visual frameworks for deployment across internal support and risk teams.
Ecosystem Intelligence for Global E-Commerce
Medusa is Alyssa’s network intelligence layer — designed to aggregate and analyse data across the e-commerce ecosystem. It provides retailers with actionable insights by leveraging shared intelligence on customer behaviours, market trends, and fraud signals. Medusa empowers smarter decisions, competitive positioning, and reduced operational risk — by turning fragmented signals into strategic clarity.
Collaborated with clients and partners to identify value gaps in siloed retail intelligence.
Mapped data flows across ecosystems to define the architecture of shared visibility without compromising privacy.
Developed strategic use cases to demonstrate the ROI of ecosystem-level intelligence in fraud detection, CX, and pricing.
Engineered Medusa as an embedded module within the Alyssa platform.
Aggregates cross-merchant behavioural, logistics, and claim data to detect patterns and shared anomalies.
Delivers real-time insights through trend visualisation, fraud pattern mapping, and peer-informed scoring logic.
Designed the Medusa interface to convey network-level insights clearly and intuitively.
Built a visual language for ecosystem intelligence that blends analytics with accessibility.
Produced product narrative assets, demo visuals, and executive-facing collateral to position Medusa as a strategic intelligence layer — not just a reporting tool.
Customer Information Lookup & Digital Identity Verification
Hannibal is Alyssa’s intelligence module for verifying customer legitimacy through data enrichment and behavioural profiling.It performs real-time digital lookups using signals such as email presence, IP behaviour, social activity, and device metadata — enabling fraud teams to distinguish between high-risk and verified users without added friction.
Worked with fraud, compliance, and onboarding teams to understand gaps in existing KYC and customer validation processes.
Defined risk typologies based on signal reliability, identity spoofing patterns, and synthetic fraud indicators.
Delivered an operational framework for layered customer verification without increasing cost or customer friction.
Built Hannibal as an embedded, modular API service within Alyssa’s infrastructure.
Performs cross-source lookups on email, device fingerprinting, IP geolocation, and social presence to generate identity confidence scores.
Enables real-time flagging and internal alerts for onboarding, transaction review, and account lifecycle events.
Designed a UI panel that allows ops and compliance teams to review digital identity profiles in seconds — not minutes.
Built a signal confidence interface with expandable attribution, metadata, and score rationale for auditability.
Produced internal training visuals and external explanation layers to simplify how digital lookup logic integrates into decisioning workflows.
Delivery Intelligence and Logistics Insight
Hamilcar is Alyssa’s delivery tracking and logistics analysis module, built to give retailers real-time visibility across their shipping operations. It monitors delivery performance, identifies inconsistencies, and supports faster resolution of customer claims — all while enhancing operational efficiency and trust.
Worked with retail logistics teams to map existing delivery workflows and identify blind spots in the post-checkout experience.
Defined failure points tied to missed scans, inconsistent carrier data, and weak tracking integrations.
Established process logic for flagging anomalies and feeding logistics signals into claims and fraud workflows.
Integrated Hamilcar as a real-time delivery intelligence layer within Alyssa.
Ingests logistics data across carriers to track parcels, validate delivery confirmation, and detect inconsistencies.
Supports downstream tools like Athena by providing signal context for delivery-related customer claims.
Designed the Hamilcar UI to present shipment-level diagnostics with clarity and speed.
Built visual tools for ops teams to monitor delivery status, flag risks, and resolve claims without external systems.
Produced explanatory content and training assets to embed Hamilcar usage into CX and logistics teams.
Product Performance Intelligence and Visual Analytics
Atlas is Alyssa’s analytics engine — designed to transform raw product data into strategic insights. It empowers retailers to track performance, identify trends, and optimise product strategies through real-time reporting, KPI dashboards, and category-level intelligence.
Partnered with retail and product teams to define key metrics tied to profitability, sell-through, and margin velocity.
Mapped the internal data environment to identify gaps in insight delivery, latency, and reporting overhead.
Built a prioritised product intelligence framework for driving commercial decisions and forecasting accuracy.
Developed Atlas as a modular reporting engine within Alyssa, capable of ingesting and visualising product-level data at scale.
Engineered dynamic dashboards and drill-down views for performance tracking, trend detection, and margin analysis.
Integrated with retail databases to automate reporting pipelines and reduce manual analyst load.
Designed the Atlas UI for clarity, speed, and decision-readiness — optimised for leadership teams, analysts, and buyers.
Built visual narratives that convert analytics into business signals — accessible in real-time and boardroom-ready.
Produced reporting templates, presentation packs, and training assets to drive internal adoption across merchandising and strategy.
CO₂ Emission Insights and Responsible Return Intelligence
Gaia is Alyssa’s sustainability module — built to help retailers analyse return patterns, measure CO₂ impact, and optimise logistics for environmental responsibility. It enables brands to reduce emissions, design greener operations, and build customer trust through transparent sustainability practices.
Worked with supply chain and sustainability teams to identify the carbon impact of reverse logistics and return flows.
Developed models for CO₂ estimation based on transportation modes, return frequency, and product categories.
Provided sustainability roadmaps that align return policies with environmental goals and brand positioning.
Engineered Gaia to analyse return patterns and calculate associated CO₂ emissions using real-time logistics data.
Provides actionable recommendations to optimise packaging, reduce transit emissions, and reroute returns efficiently.
Feeds sustainability metrics into broader operational dashboards for visibility and ESG reporting.
Designed Gaia’s UI to clearly communicate environmental data and impact scenarios to both internal teams and external stakeholders.
Created visual assets for brands to showcase sustainability metrics transparently to customers.
Developed comms toolkits to position Gaia-integrated brands as forward-thinking and environmentally accountable.
Modular Intelligence Platform for Retail Risk, Ops & Strategy
Alyssa is E-Sentinel’s core SaaS platform — a modular infrastructure layer designed to help retailers combat fraud, optimise operations, and make better strategic decisions across the full customer journey.
Each embedded module within Alyssa (Athena, Medusa, Hannibal, Hamilcar, Atlas, and Gaia) addresses a critical friction point, creating a unified control system for retail execution and resilience.
Engaged with retail stakeholders to deconstruct the full commerce lifecycle — from account creation to post-purchase returns.
Identified systemic inefficiencies, fragmented tooling, and reactive fraud processes.
Defined a modular delivery model that enables retailers to scale capability in phases, without disrupting operations.
Built Alyssa as a modular SaaS infrastructure, engineered for high-volume, multichannel retail environments.
Each module is deployable independently or as part of a unified platform — fully API-enabled, compliant, and scalable.
The system leverages behavioural data, operational signals, and ecosystem intelligence to automate decisioning and surface risk.
Developed a platform brand identity centred on intelligence, modularity, and precision.
Designed the Alyssa UI as a control layer: functional, accessible, and adaptable across teams — from fraud to CX to strategy.
Created launch materials, module-specific narratives, and visual frameworks to support internal adoption and external positioning.
Agentic AI Assistant for Internal Ops and Decision Support
Mr M is Alyssa’s internal agent — a large language model–orchestrated system that interprets data, initiates tasks, and autonomously supports operational teams. Designed with multi-agent logic, Mr M reduces the need for human intervention in complex workflows by generating insights, recommending actions, and coordinating internal processes in real time.
Worked with operational leads to identify high-frequency, low-leverage tasks consuming team bandwidth.
Mapped internal logic chains and decision trees to define the orchestration architecture needed for autonomous execution.
Defined a governance model for oversight, escalation, and risk control within AI-driven internal operations.
Built using a multi-agent architecture leveraging LLMs, vector memory, and tool-based execution.
Integrated Mr M across data layers, dashboards, and decision points — enabling real-time lookup, task resolution, and insight generation.
Supports plug-in orchestration with external APIs and internal systems for true cross-function automation.
Crafted a lean interface for Mr M that allows users to interact conversationally, trigger actions, and visualise system decisions.
Developed prompt design layers and context feeds to maximise precision and minimise hallucination.
Created internal communication assets to train teams on safe usage, oversight boundaries, and escalation triggers.
Real-time fraud detection for retail and marketplaces
Alyssa is a comprehensive suite of AI-driven tools designed to prevent fraud, optimize operations, and enhance decision-making for e-commerce businesses. Each product within Alyssa tackles a specific challenge, from fraud detection to operational efficiency.
Engaged with retail stakeholders to deconstruct the full commerce lifecycle — from account creation to post-purchase returns.
Identified systemic inefficiencies, fragmented tooling, and reactive fraud processes.
Defined a modular delivery model that enables retailers to scale capability in phases, without disrupting operations.
Built Alyssa as a modular SaaS infrastructure, engineered for high-volume, multichannel retail environments.
Each module is deployable independently or as part of a unified platform — fully API-enabled, compliant, and scalable.
The system leverages behavioural data, operational signals, and ecosystem intelligence to automate decisioning and surface risk.
Developed a platform brand identity centred on intelligence, modularity, and precision.
Designed the Alyssa UI as a control layer: functional, accessible, and adaptable across teams — from fraud to CX to strategy.
Created launch materials, module-specific narratives, and visual frameworks to support internal adoption and external positioning.
About Us
We are a delivery firm led by senior operators, technologists, and designers with experience spanning regulated industries, venture-backed growth, and strategic transformation.
Alastra Labs builds the systems behind high-growth companies and enterprise-scale operations.
Where We Work. How We Think.
Where We Work. How We Think.
Values & Behaviours
Alastra Labs operates according to a set of core principles that guide all client engagements, internal processes, and strategic decisions.
We design systems where complexity serves function, not itself. Every model, framework, and solution maintains intellectual coherence at all levels of scale.
Our work moves at the optimal pace—fast enough to create momentum, deliberate enough to ensure precision. Each deliverable is evaluated against measurable outcomes.
We build functional systems, not conceptual models. Our solutions are designed to operate under real conditions, creating lasting structural advantage.
Engagement continuity is non-negotiable. The teams that design solutions remain accountable through implementation, ensuring integrity between concept and execution.
We maintain institutional discipline by eliminating structural inefficiencies. This creates the conditions for autonomous, high-velocity execution within a framework of alignment.
Our methodologies combine rigorous analysis with field-tested implementation. We integrate emerging capabilities only when they demonstrably enhance outcomes.