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COMPLIVISE

Your process.
Your intelligence.
Your system.

COMPLIVISE connects pharmacovigilance, regulatory, labelling and quality — so one change is assessed, assigned, actioned and evidenced in one place.

A Spearhub Initiative · Technology delivery since 2019 · Hyderabad, India

5+
Intelligence solutions
50+
Configured workflows
100+
Data sources integrated
100%
Validated processes
ONE
Connected platform

Track record, platforms and standards

Regulated pharmaceutical systems built since 2019 — on qualified cloud infrastructure, against the standards inspectors actually audit.

  • GPGlobal Pharma GroupSafety operations, 14 markets
  • NBNordic BiologicsRegulatory intelligence
  • ALAurora LabsLabelling change control
  • MCMeridian Consumer HealthQuality deviations
  • SVSentinel VigilanceLiterature monitoring
  • KTKestrel TherapeuticsQPPV oversight
  • IXIndus FormulationsSubmission readiness
  • OROrbis Rare DiseaseSignal management
  • GPGlobal Pharma GroupSafety operations, 14 markets
  • NBNordic BiologicsRegulatory intelligence
  • ALAurora LabsLabelling change control
  • MCMeridian Consumer HealthQuality deviations
  • SVSentinel VigilanceLiterature monitoring
  • KTKestrel TherapeuticsQPPV oversight
  • IXIndus FormulationsSubmission readiness
  • OROrbis Rare DiseaseSignal management
  • AWSAmazon Web ServicesGxP-qualified hosting
  • GCPGoogle CloudRegional data residency
  • AZMicrosoft AzurePrivate tenant deployment
  • DBDatabricksSafety and literature data
  • SFSnowflakePortfolio and market data
  • HL7HL7 FHIR R4Clinical data exchange
  • E2BICH E2B(R3)ICSR exchange
  • IDMPISO IDMPProduct data model
  • VLTVeeva VaultDocument and RIM integration
  • SAPSAP QMQuality event integration
  • AWSAmazon Web ServicesGxP-qualified hosting
  • GCPGoogle CloudRegional data residency
  • AZMicrosoft AzurePrivate tenant deployment
  • DBDatabricksSafety and literature data
  • SFSnowflakePortfolio and market data
  • HL7HL7 FHIR R4Clinical data exchange
  • E2BICH E2B(R3)ICSR exchange
  • IDMPISO IDMPProduct data model
  • VLTVeeva VaultDocument and RIM integration
  • SAPSAP QMQuality event integration

Built to operate under

  • 21 CFR Part 11Electronic records and signatures
  • EU GMP Annex 11Computerised systems
  • GAMP 5 (2nd ed.)Risk-based validation, AI/ML appendix
  • GVP Modules VI & IXICSR management and signal detection
  • ICH E2B(R3)ICSR transmission
  • ISO IDMP / SPORSubstance, product, organisation, referential
  • MedDRA & WHO-DDCoding dictionaries
  • HL7 FHIR R4Interoperability
  • ICH Q9(R1) / Q10Quality risk management
  • ISO 27001 & ISO 13485Information and quality management
  • GDPR / HIPAAPersonal and health data protection
  • EU AI Act (GPAI)Transparency and human oversight
01Common challenges, smarter solutions

The problems MAHs and sponsors actually raise.

What teams tell us — and what COMPLIVISE does about it.

  • Regulatory change arrives faster than teams can assess it.

    Impact assessment, CMC gap analysis and label actions in one place.

  • Signal work stalls across FAERS, VigiBase and internal data.

    Multi-database extrapolation with case series and causality review, qualitative signal detection and assessment.

  • MICC , Literature screening, ICSR and aggregate live in separate tools.

    Safety Information-to-ICSR as unified path with XML and aggregate support.

  • CCDS comparison shows differences but not consequences.

    Comparison tied to market impact, CSI preparation and owners.

  • Manual, repetitive steps create delay and rework.

    Configurable workflows that automate the routine, not the judgement.

  • Scattered documents leave audits without a traceable story.

    Centralised evidence and end-to-end, inspection-ready audit trail.

COMPLIVISE turns those challenges into controlled, intelligent and compliant outcomes.

02The operating model

From information to action. From evidence to impact.

Every product follows the same five stages.

  1. 01

    Information

    Literature, safety sources, studies, RWE, regulatory updates, labels and quality records.

  2. 02

    Intelligence

    Search, extraction, screening, comparison, classification and monitoring.

  3. 03

    Impact

    Patient-safety, product, regulatory, risk assessment, labelling and quality implications.

  4. 04

    Action

    Case processing, label updates, submissions, CAPA and change control.

  5. 05

    Evidence

    Sources, decisions, approvals, ownership, version history and completion records.

Pharmacovigilance, regulatory, labelling and quality. Not clinical development.

04Connected impact

One regulatory change, followed to closure.

Four functions, no re-keying, one unbroken evidence chain.

  1. 01

    Regulatory Intelligence

    A new authority communication is detected

    Monitoring picks up a published safety communication and records the source, publication date and issuing authority.

    REG-2026-0192 · published 11 Aug

  2. 02

    Regulatory Intelligence

    Relevance is assessed against the portfolio

    The substance class is matched to marketed products; a reviewer confirms relevance and records the rationale.

    2 products in scope · reviewer confirmed

  3. 03

    Signal Intelligence

    Associated cases and literature are identified

    Existing ICSRs and screened literature records carrying the same event term are retrieved and attached.

    9 cases · 3 literature records linked

  4. 04

    Label Intelligence

    Affected label sections and markets are identified

    CCDS section 4.4 is compared against regional labels; two markets require wording changes, one is already aligned.

    Section 4.4 · 3 markets assessed

  5. 05

    Quality Intelligence

    Controlled actions are created

    A CAPA and a change-control record are raised, linked back to the originating regulatory update.

    CAPA-2026-118 · CC-2026-047

  6. 06

    Across all layers

    Owners, due dates and reviewers are assigned

    Each action has a named owner, a due date and a second reviewer where maker-checker is configured.

    6 actions · 4 owners · 2 reviewers

  7. 07

    Evidence

    Completion evidence is retained

    The source, assessments, decisions, approvals and closure records stay connected to the original change.

    Complete chain retained

Illustrative product experience, based on a routine safety communication.

05Case studies

Before and after, mapped step by step.

Four workflows as they run today, and the same workflows connected. Illustrative maps — no client names.

Safety-article intake from literature and shared mailboxes to ICSR

Reports arrive as email bodies, scanned forms, partner spreadsheets and literature records. Case creation depends on one associate reading each item and re-typing it into the safety database.

Before — how the work runs today

  1. B1

    Mailbox

    Mixed formats, no queue position

  2. B2

    Manual triage

    Read, judge validity, decide priority

  3. B3

    Spreadsheet log

    Parallel tracker outside the database

  4. B4

    Email handoff

    Medical review requested by message

  5. B5

    Database entry

    Fields re-keyed from the source

After — with COMPLIVISE in the workflow

  1. A1

    Intake

    Literature, mailboxes and partner files land in one queue

  2. A2

    Assisted extraction

    Fields proposed with source excerpts

  3. A3

    Assessment

    Validity, seriousness, duplicate evaluation

  4. A4

    Assigned review

    Named medical reviewer, due date

  5. A5

    Structured handoff

    ICSR XML export with retained provenance

Where it breaks down

  • Validity and seriousness decisions live in an individual's judgement, not in a record.
  • Duplicate reports are found late, after data entry has already happened.
  • The link between a database field and the sentence it came from is lost.

What the system performs

  • Patient, reporter, product and event elements are extracted and shown beside the source text.
  • Case validity and seriousness are assessed as recorded steps a reviewer confirms or amends.
  • Duplicate candidates are surfaced before entry, with the rationale kept either way.

Evidence retained

  • Source document and received timestamp
  • Extraction provenance per field
  • Reviewer amendments with identity
  • Seriousness and validity rationale
  • ICSR XML export receipt to the safety database
  • Case status is visible per source rather than per person.
  • Every entered field can be traced back to the sentence it came from.
06Platform foundation

One configurable foundation beneath every layer.

One shared platform: configuration replaces custom rebuilds, and the same controls apply everywhere.

Configuration

  • Configurable forms
  • Configurable workflows
  • Assignment and escalation
  • Notifications and due dates
  • White-labelling

Control

  • Role-based access
  • Maker-checker review
  • Source-evidence linking
  • Version history
  • Configurable audit trails

Operation

  • Dashboards and analytics
  • API integrations
  • Private-cloud deployment
  • On-premise deployment options
  • Multi-tenant architecture
07AI approach and trust

AI that shows its evidence, and a human who remains accountable.

An answer without its source is not usable. AI accelerates reading and classification; qualified professionals make the decisions that carry regulatory weight.

Evidence-grounded review — proposed extraction

Case SAF-2026-0841 · source: reporter narrative, page 2

Source passage

“The patient was admitted to hospital for three days following the second dose and was discharged in a stable condition.”

The highlighted passage is the only basis for the proposal on the right.

Proposed for review

Seriousness
Serious — hospitalisation
Confidence
0.88
Reviewer
A. Kulkarni — required
AcceptAmendEscalate

Whichever the reviewer chooses is recorded with their identity, the original proposal and the timestamp.

Illustrative product experience. AI proposes; a qualified professional decides.

Governance principles

Evidence-linked outputs
Every important output can be traced to the source passage it came from.
Human decision authority
AI proposes; a qualified professional accepts, amends or escalates.
Confidence and exception handling
Low-confidence and incomplete extractions are routed to review rather than accepted silently.
Role-based access
Who can view, assess, approve and export is defined per role and per workflow step.
Traceability
Inputs, outputs, amendments and approvals can be recorded with reviewer identity and timestamp.
Model and prompt governance
Models, prompts and evaluation criteria are versioned and deliberately managed.
Fit-for-purpose implementation
Controls are designed around intended use and the risk of the specific workflow.
Secure deployment options
Private-cloud and on-premise deployment, data segregation and encryption in transit and at rest.
Validation-support documentation
Specifications, configuration records and test evidence to support customer validation activities.

Security and quality controls

  • Secure development practices
  • Role-based access
  • Encryption in transit and at rest
  • Data segregation
  • Configurable audit trails
  • Backup and recovery planning
  • Private-cloud options
  • On-premise options
  • Controlled AI data handling
  • Model evaluation
  • Integration governance
  • Validation-support documentation

Technical controls, validation activities and regulatory requirements depend on the system's intended use, deployment configuration and the customer's operating procedures. COMPLIVISE works with customers to define and support the appropriate controls and documentation.

Take this with you

The AI Evaluation Checklist for Pharmaceutical Teams

Twelve questions on intended use, traceability, human review and validation. Use it against any vendor — including us.

08Readiness assessment

Where does your organization actually stand?

Nine questions, three minutes. Your result appears immediately — details only if you want the written brief.

Question 1 of 9

Information fragmentation

How many systems or manual sources are involved in completing a typical assessment?

09In development

What we are building next, stated plainly.

Not shipping today. Active development areas where a co-development partner shapes what is built first.

07Co-development

Aggregate Reporting Intelligence

PSUR/PBRER preparation from source collection and reconciliation through drafting support and approval.

  • PSUR/PBRER workflow
  • Source collection
  • Evidence retrieval
  • Data reconciliation
  • AI-assisted drafting
  • Benefit-risk review support
  • Collaboration
  • Version control
  • Approval workflow
08Roadmap

Submission Intelligence

Requirement mapping and gap identification across CMC, stability, analytical and labelling content before filing.

  • Requirement mapping
  • Missing-document identification
  • CMC gaps
  • Stability-data gaps
  • Analytical gaps
  • Labelling gaps
  • ANDA gap analysis
  • Submission-readiness assessment
10Engagement and partnership

Adopt, configure, extend, white-label or build.

You rarely need a platform rebuild. You need one workflow to work properly, then the next.

  1. 01

    Adopt

    Deploy a COMPLIVISE product accelerator.

  2. 02

    Configure

    Adapt terminology, fields, workflows, roles, rules and reports.

  3. 03

    Extend

    Add organization-specific modules, analytics and integrations.

  4. 04

    White-label

    Launch selected solutions under the client's identity and operating model.

  5. 05

    Build

    Co-develop a custom safety, regulatory, labelling or quality platform.

Domain-led

Solutions begin with the pharmaceutical workflow—not a generic AI capability.

Product-driven

Reusable platforms create faster implementations and stronger long-term foundations.

Flexible delivery

Choose pre-built products, configuration, white-labelling or custom development.

Long-term partnership

Strategy, design, engineering, integration, deployment and managed support from one team.

Workflow mapping session

45 minutes on one workflow, mapped end to end.

We map the current sequence — sources, decisions, handoffs, owners and evidence — and show you where effort and latency actually sit. No obligation, and no slideware.

Optional — helps us prepare.

Company

“Pharmaceutical teams do not need more dashboards. They need the distance between knowing something and having acted on it to get shorter — without losing the record of how the decision was made.”

Founder’s position · COMPLIVISE, A Spearhub Initiative

COMPLIVISE is the pharmaceutical intelligence practice of Spearhub, a technology company delivering enterprise platforms, applied AI and workflow systems since 2019. The practice exists because pharmacovigilance, regulatory, labelling and quality teams share the same underlying problem, and almost never share a system.

  1. 2019

    Spearhub technology-delivery journey begins

  2. Product Engineering

    Enterprise platforms, mobile products, cloud systems and automation

  3. Applied AI

    Intelligent search, document processing, workflow automation and agent-based systems

  4. COMPLIVISE

    Dedicated pharmaceutical intelligence practice

11Start a conversation

Tell us about one workflow.

Describe the workflow that costs your team the most time. We will tell you honestly whether we fit.

Based in
Hyderabad, India
Practice of
A Spearhub Initiative