Clinical Study Report drafting and review automation
We help teams speed up CSR development by extracting data from protocols, SAPs, and TLFs, generating structured ICH E3-compliant drafts, and supporting review with source-linked traceability and feedback-aware updates.
Powering faster, compliant life sciences workflows with Generative AI and a connected data foundation
Shorthills AI helps life sciences teams bring together the data they already have across quality, manufacturing, clinical, and regulatory systems and then help them turn it into faster, more usable insight. On top of this connected foundation, we add an agentic AI layer that helps teams draft reports, answer cross-system questions, and reduce the manual effort involved in highly regulated workflows.
Whether the need is speeding up Annual Product Quality Reviews, enabling plain-English access to manufacturing and quality data, or accelerating Clinical Study Report drafting, we help teams move faster without compromising traceability, review control, or compliance. RxHorizon is positioned as a shared architecture across RxPQR, RxGaze, and RxCSR, while RxCSR specifically focuses on ICH E3-compliant CSR drafting from protocols, SAPs, and TLFs.
APQR and quality reporting automation
We automate Annual Product Quality Reviews by pulling data, running CPK, PPK, and trend analysis, generating charts, and drafting interpretations so teams can review reports the same day instead of waiting weeks.
We work with pharma, biotech, medical writing, quality, and regulatory teams to reduce manual work, improve traceability, and make complex data easier to use across the product and study lifecycle.
Powering smarter, faster healthcare with Generative AI and a centralized data hub
Shorthills AI helps healthcare organizations turn complex clinical, genetic, and insurance data into clear, decision-ready insight—without adding more burden on clinicians or staff. We build centralized data hubs that bring together Electronic Health Records (EHR), claims, lab reports, and genetic information into one trusted foundation, then layer GenAI tools on top to reduce manual work, improve accuracy, and speed up critical workflows.
Whether you’re digitizing genetic workflows, improving patient intake, or modernizing a country-wide healthcare and insurance platform, we help you move faster with secure, governed AI built for real-world healthcare—where safety, privacy, and compassion matter as much as speed.
Natural-language access to manufacturing and quality data
We build AI layers that let teams ask manufacturing and quality questions in plain English across connected systems, with source citations down to the exact table, row, and column.
Compliance-ready, traceable AI workflows
Our life sciences solutions are built around audit trails, role-based access controls, e-signatures, and human-in-the-loop review so teams can adopt AI in a way that fits regulated environments.
Scalable support for medical writing and regulatory teams
We help medical writing and regulatory teams automate the heavy lift of extraction, transcription, consistency checks, and cross-document review so experts can focus on interpretation and final sign-off.
Unified clinical, claims, and operational data hub
Bringing together EHR feeds, ADT messages, claims, and legacy data into a single, trusted platform—so providers and administrators see the full patient journey instead of piecing it together from multiple systems.
Risk scoring, cost-of-care, and population health analytics
Clean, unified data powers models that estimate care costs, identify high-risk patients, and support value-based care — reducing readmissions and insurance costs.
Genetic pedigree digitization and rare-disease workflows
Turning hand-drawn pedigree charts into structured, editable digital records and building tools that make it easier to capture, store, and reuse genetic family history at scale.
Patient intake and family history automation
Using guided chatbots and AI forms to collect family and medical history ahead of appointments, so consultations focus on decision-making instead of basic data capture.
Medical evidence synthesis and patient-friendly guides
Applying LLMs to trusted medical literature to draft accurate, sensitive, patient-friendly guides—helping teams move from months of manual reading to minutes per first draft, while keeping experts in the loop.
Security, privacy, and governance for healthcare AI
Designing solutions that respect HIPAA, GDPR, and local data rules—from encryption and access controls to on-prem or client-controlled hosting—so sensitive health data stays protected end-to-end.
Our Focus Areas in Retail
Turning Retail’s Biggest Challenges into Opportunities
Retailers that win see what’s happening now and act fast. Shorthills AI turns fragmented systems and slow reports into a real-time, AI-ready retail backbone.
From batch reports to real-time insight
We replace slow, on-prem reporting with cloud-native streaming, enabling sales, returns, and inventory to have one real-time view.
From siloed data to a true 360° view
We connect web, POS, loyalty, and marketing data into one model for clear customer and product visibility.
From ad-hoc analytics to ML-ready foundations
We build clean, trusted datasets that power dashboards and AI use cases like churn, recommendations, and demand forecasting.
From manual effort to AI-assisted decisions
We add secure GenAI assistants so teams can ask questions in plain English and get instant, actionable answers.
From risky transformation to governed modernization
We use proven methods, encryption, and access controls to modernize data safely and get you ready for the next wave of AI.
Life Sciences Challenges We See Most Often
Life sciences teams already have the data and documents they need. The bigger problem is that these sit across too many systems, take too long to pull together, and still require too much manual effort before they become useful.
Siloed data across too many systems
Critical data is spread across manufacturing, quality, clinical, and regulatory systems, making it hard for teams to pull together a complete picture when they need it most.
Slow, manual CSR drafting and review
Creating Clinical Study Reports still involves heavy manual extraction, drafting, checking, and redrafting across protocols, SAPs, and TLFs, which slows timelines and increases rework. RxCSR describes this as moving from 8–12 weeks of manual drafting to 2–3 weeks of focused review.
Time-heavy APQR and quality reporting cycles
Quality teams spend too much time gathering data, preparing charts, and writing interpretations by hand, which delays reporting and pulls attention away from improvement work.
Too much system-hopping for basic answers
Teams often have to move across multiple tools and ask technical teams for help just to answer straightforward quality or manufacturing questions.
High compliance expectations with little room for error
In regulated environments, every output needs strong traceability, auditability, and controlled review, so generic AI tools often do not fit the level of rigor required. RxHorizon highlights 21 CFR Part 11 alignment, while RxCSR emphasizes ICH E3 structure and source-grounded drafting.
Experts spending time on manual effort instead of expert judgment
Medical writers, QC leads, and SMEs often spend too much time on extraction, formatting, and cross-checking, when their real value lies in interpretation, review, and final decision-making.
Our Focus Areas in Life Sciences
Turning Life Sciences’ Biggest Challenges into Opportunities
From disconnected systems to one shared intelligence layer
We add a connected data foundation and AI layer on top of the systems teams already use, so data becomes easier to access and work with without forcing a major process change.
From weeks of CSR drafting to faster, structured review
RxCSR helps teams move from manual CSR creation toward AI-assisted drafting that is structured around ICH E3 sections, grounded in source documents, and designed for expert review rather than blind automation.
From manual APQR effort to same-day review readiness
We automate the heavy work of pulling data, running analysis, generating charts, and drafting interpretations so quality teams can review reports much faster. RxHorizon says RxPQR can reduce APQR generation time by 80%.
From system-hopping to plain-English answers with traceability
With RxGaze-style cross-system querying, teams can ask questions in natural language and get instant answers with citations, reducing dependency on SQL, IT tickets, and manual searching.
From compliance risk to audit-ready AI workflows
We build AI workflows with audit trails, source grounding, access controls, and human-in-the-loop review so life sciences teams can adopt automation while staying aligned with regulatory expectations.
From manual heavy lifting to higher-value expert work
By automating extraction, drafting, validation, and consistency checks, we free up medical writers, regulatory teams, and quality experts to focus on scientific judgment, interpretation, and final sign-off. RxCSR explicitly positions itself as an accelerator, not a replacement for medical writers or SMEs.
Life sciences organizations that can connect their data and apply AI in a controlled way can move faster without losing rigor. Shorthills AI helps turn slow, manual, system-heavy processes into connected workflows that are easier to review, scale, and trust.
Omnichannel data backbone & real-time analytics
Unifying e-commerce, POS, inventory, and marketing data into a governed lakehouse on platforms like Azure Databricks—so leaders get real-time visibility into sales, margins, and stock across channels, stores, and regions.
Customer 360 and AI-driven personalization
We combine what customers do, what they buy, and how they interact into one complete customer profile, then using GenAI and ML to power smarter segmentation, recommendations, next-best-offer journeys, and retention programs.
Demand forecasting, inventory & assortment optimization
Using machine learning on historical sales, promotions, seasonality, and external signals to forecast demand, optimize inventory levels, and fine-tune assortments—reducing stockouts, overstock, and margin leakage.
Pricing & promotion intelligence
We analyze sales and market signals to find the best prices and promotion plans across channels — helping teams protect margins while staying competitive and quick to respond to market changes.
Store performance & operational intelligence
We pull together sales, staffing, and operations data to show store-level insights — like productivity, conversion rates, and losses. AI assistants and dashboards help managers spot problems early and fix them fast.
GenAI copilots for retail teams
Building secure, domain-tuned GenAI copilots that sit on top of your governed data—helping planners, marketers, and operations teams query data in natural language, generate insights, and automate routine analysis and reporting.
Our Focus Areas in Retail
Cross-system data unification for life sciences
We connect data across systems like LIMS, MES, QMS, DMS, ERP, SAS, OneDrive, and FTP sources, creating one shared data foundation without forcing teams to change their existing workflows.