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Your R&D Data Has Answers. We Help You Find Them.

We build AI systems that make pharmaceutical R&D, quality, and regulatory data searchable and usable — deployed on your infrastructure, never in the cloud.

See CDMO Case Study →
10+
Years of R&D data made searchable
60%
Faster formulation decisions
CDMO
Proven at a leading Indian CDMO
On-Prem
Your IP never leaves your infrastructure

Four AI Systems. Built for Drug Development.

Purpose-built for the data challenges that slow down formulation scientists, regulatory teams, and quality operations.

[01]

R&D Knowledge Search

Make 10+ years of formulation studies, stability data, and lab notebooks instantly queryable — so scientists stop reinventing what your organization already knows.

  • Semantic search across proprietary R&D documents and studies
  • Query formulation records, excipient data, and trial outcomes in natural language
  • Surface related historical studies automatically during new formulation work
  • Reduce repeat experiments by connecting scientists to existing institutional knowledge
Stop Reinventing Speed Formulation Protect IP
CDMOs Generics R&D API Manufacturers
[02]

Regulatory Dossier Intelligence

Convert unstructured regulatory documents — CTD modules, NDA/ANDA submissions, stability reports — into structured, searchable data that accelerates submissions and gap analysis.

  • Auto-extract and structure data from CTD Module 2, 3, 4, and 5 documents
  • Identify gaps between current data packages and regulatory requirements
  • Cross-reference study data against ICH guidelines automatically
  • Generate structured summaries of clinical and non-clinical sections
Faster Submissions Gap Detection Audit-Ready
Regulatory Affairs NDA/ANDA CDSCO / FDA / EMA
[03]

Quality & Deviation Analytics

Detect Out-of-Specification patterns, surface CAPA trends, and connect batch deviations to root causes — before they escalate into observations or warning letters.

  • Anomaly detection across batch records, OOS events, and deviation logs
  • Pattern analysis across CAPA history to identify recurring root causes
  • Auto-link deviations to related investigations and corrective actions
  • Full audit trail linking findings back to source batch records
Catch OOS Early Reduce Repeat Deviations Audit Confident
QA / QC GMP Manufacturing CAPA Management
[04]

Pharmacovigilance Signal Intelligence

Aggregate and analyze adverse event reports, HCP communications, and literature signals to surface safety concerns before they become regulatory obligations.

  • Analyze AE narratives across MedWatch, VigiBase, and internal safety databases
  • Natural language processing on medical affairs communications and field reports
  • Signal detection and disproportionality analysis across large case volumes
  • Auto-classify and prioritize cases for medical review
Early Signal Detection Reduce Manual Review Stay Compliant
Medical Affairs Drug Safety Post-Market Surveillance

From Siloed R&D Data to an Institutional Knowledge Engine

How a leading Indian CDMO gave its formulation scientists the ability to search a decade of proprietary R&D data in seconds

CLIENT Encube Ethicals — Leading CDMO, India

The Problem

Encube Ethicals, a leading contract development and manufacturing organization, had accumulated over a decade of proprietary R&D data — formulation studies, stability reports, excipient compatibility data, clinical batch records, and regulatory submissions. This knowledge lived across shared drives, lab notebooks, and disconnected document management systems.

When formulation scientists began new drug development projects, they had no reliable way to query what the organization already knew. Teams were unknowingly duplicating studies, starting formulations from scratch when relevant historical data existed, and losing weeks to knowledge retrieval that should have taken minutes.

The Solution

  • Deployed an on-premise AI-powered structured search system over Encube's entire R&D document corpus — no data left their infrastructure
  • Built a semantic search layer that understands pharmaceutical terminology, enabling natural language queries like "show me stability studies for semi-solid formulations with carbomer base"
  • Connected structured outputs (formulation parameters, excipient grades, study outcomes) with unstructured narrative reports so scientists get complete context, not just document links
  • Implemented role-based access controls so proprietary client formulation data remained appropriately siloed while enabling cross-project knowledge sharing within permitted boundaries

The Impact

60%
Faster Formulation Decisions
10+ yrs
R&D Data Now Searchable
Zero
Data Left Infrastructure

"Our scientists can now query what we already know before starting any new formulation project. It has fundamentally changed how we reuse institutional knowledge."

— R&D Leadership, Encube Ethicals

Every pharma R&D organization is sitting on a goldmine of proprietary data that no one can effectively search. The challenge isn't generating data — it's making existing knowledge findable at the moment scientists need it most.

— Soumya Sharma, Co-Founder, Livo.AI

Three Steps. Zero Risk. Full IP Protection.

We start with two completely free steps. Every engagement is under NDA and deployable fully on-premise before you commit a rupee.

01

Free Pharma AI Workshop

A focused session with your R&D, regulatory, or quality team to identify the highest-value AI use cases in your organization. We bring pharma-specific frameworks. No sales pitch — just strategic clarity.

100% Free
02

Free AI Roadmap

We deliver a prioritized implementation roadmap with ROI estimates specific to your molecule pipeline, manufacturing scale, and regulatory markets. Yours to keep with no obligation.

100% Free
03

Pilot on Your Data

We build a working pilot on your actual data, deployed inside your infrastructure. You see results before you sign anything beyond the pilot scope. You're always in control.

Your Decision

Ready to See What's Inside Your R&D Data?

Book your free workshop. Bring your R&D head, your regulatory lead, or your QA director — we'll map exactly where AI creates the highest impact for your organization.

Built for the Compliance Reality of Drug Development

Pharma IP is your most valuable asset. Every system we deploy is designed to keep your data, your formulations, and your regulatory submissions inside your own walls.

🔒

On-Premise Deployment — IP Protection First

Your proprietary formulations, R&D data, and regulatory documents never touch a cloud environment. Full deployment inside your data center or private cloud. We bring the system to your data — not the other way around.

📋

21 CFR Part 11 Compatible

Systems designed with electronic records and electronic signatures requirements in mind. Full audit trails, access controls, and data integrity measures compatible with FDA electronic records standards for regulated environments.

GxP Data Integrity Principles

Built around ALCOA+ principles — Attributable, Legible, Contemporaneous, Original, Accurate. Every data interaction is traceable. Designed to survive an FDA data integrity inspection without surprises.

🧪

ICH Q10 Pharmaceutical Quality System

AI systems structured around ICH Q10 quality management lifecycle — supporting continual improvement, CAPA management, and knowledge management across drug development and manufacturing.

🇮🇳

DPDP Rules India (2025) Compliant

Data processing and storage of Indian citizens on India servers. Full compliance with India's Digital Personal Data Protection Act — critical for Indian pharma companies handling patient or HCP data.

🌐

GDPR Compliant

Privacy and data protection by design for pharma companies with EU regulatory submissions, clinical trial data, or European manufacturing operations.

Pharma AI Expertise Without the Big Consulting Price Tag

Pharma AI is a specialized capability. Most AI vendors don't understand GxP. Most pharma consultants don't understand AI. We sit at the intersection.

Aspect
Big Consulting / SaaS AI Tools
Livo.AI for Pharma
Pharma Domain Knowledge
Generic AI, pharma-specific add-ons
Built from day one for R&D & manufacturing
Data Sovereignty
Cloud-hosted, SaaS models
On-premise by default
Discovery / Workshop
₹40L–₹1.5Cr
Free
Pilot to Production
12–24 months
6–16 weeks
Team
Generalist management consultants
Senior AI engineers who've shipped pharma systems
Compliance Awareness
Bolt-on compliance layers
21 CFR 11, GxP, ICH Q10 from design

Start with zero risk. Get a pharma AI roadmap specific to your pipeline before committing a rupee.

Questions Pharma Leaders Ask Us

Everything you need to know before bringing AI into a regulated drug development environment.

Every system we build can be deployed fully on-premise inside your data center or private cloud. Your formulation data, stability studies, and batch records never leave your infrastructure. We work under NDA from first conversation. For CDMOs with multiple client formulations, we also implement role-based access controls to keep client data appropriately siloed.

We design systems compatible with 21 CFR Part 11 electronic records requirements — full audit trails, access logs, and data integrity controls are built in. We follow GxP data integrity principles (ALCOA+) by design. We don't add compliance as an afterthought; it shapes how we architect data flows from the start. For validation activities, we can provide IQ/OQ/PQ documentation support.

We work with CDMOs, generics manufacturers, API producers, and specialty pharma companies. Our Encube Ethicals engagement was with a CDMO — and the R&D knowledge search use case is directly applicable to any formulation-heavy organization sitting on years of proprietary study data. We also engage with branded pharma companies on regulatory intelligence and pharmacovigilance use cases.

Most pilots are live in 6–10 weeks. The longest part is typically data access and infrastructure setup on your side — the AI system itself builds fast once we have a clear data pipeline. Full production deployment with validation documentation typically takes 3–5 months. We won't over-promise timelines; pharma implementations have real compliance steps that take time to do properly.

Yes. We build connectors to existing document management systems (Veeva Vault, OpenText, SharePoint), LIMS platforms, SAP, and custom legacy systems. Our approach is to enhance your existing infrastructure — not replace it. The AI layer sits on top of your current systems, making their data usable without disrupting validated workflows.

A focused 2–3 hour session (remote or on-site) with your relevant functional leaders — R&D, regulatory, QA, or medical affairs depending on your priorities. We map your current data assets and workflows, identify the top 3–5 AI use cases by ROI potential, and discuss feasibility given your compliance constraints. You leave with a concrete view of where AI creates the most value for your specific organization.

We bring McKinsey-grade strategy with senior AI engineering execution

Soumya Sharma - Co-Founder

Soumya Sharma

Co-Founder

Ex-McKinsey
IIM-Ahmedabad
IIT-Delhi, Computer Science

Kangana Pandiya - Co-Founder

Kangana Pandiya

Co-Founder

Ex-McKinsey
IIM-Ahmedabad

Let's Map Your Pharma AI Opportunity

Book a 30-minute discovery call with our team. We'll identify your highest-ROI use case — whether it's R&D search, regulatory intelligence, quality analytics, or pharmacovigilance — and map out a compliant implementation path.