11 use cases01Drawing Hub
Multimodal P&ID, GA, MEP analysis. Symbol detection, GMP compliance, tag cross-ref, version diff.
Document intelligence for EPC
The AI operating layer for EPC firms.
A modular AI platform that reads, validates and acts on engineering drawings, tenders, vendor proposals and compliance documents — in real time. Built for EPC consultants and service providers.
GMP / FDA CompliantMulti-Hub PlatformRAG + LLMPharma-GradeAudit-Ready
epcfluxai.app / dashboard
70%
Drawing review time saved
5×
Faster tender response
94%
GMP compliance score
921h
Engineer hours saved / month
§ 02 · The Problem
The world runs on documents. But they don't talk to each other.
01
Contracts
Live in legal's drive. Terms rediscovered every renewal.
02
Drawings
Sit in a CAD vault. Changes ripple to specs only when remembered.
03
Quotes
Arrive as PDFs and emails. Compared in spreadsheets, by hand.
04
Compliance
Lives in audit binders. Traceability is a scramble.
A $2M RFQ moves through seven tools and four teams. No single source of truth. Approvals stall. Vendor comparisons rebuilt every project.
§ 03 · The Workflow
From document chaos to grounded output.
Engineering documents flow through your standards and your workflows — emerging as validations, compliance checks, comparisons and generated deliverables you can trust.
01 · Ingest
Documents & Drawings
Tenders, P&IDs, BOQs, vendor docs
P&IDTenderBOQVendor PDF
02 · Ground
References & Standards
Codes, specs, internal playbooks
ASHRAENBCClient SpecPast Projects
03 · Orchestrate
Custom Workflows
Your review process, automated
RouteApproveEscalateNotify
04 · Deliver
Validate · Compare · Generate
Audit-ready outputs, every time
ValidationComplianceComparisonGeneration
Speed
Weeks of review compressed into minutes
Quality
Consistent, traceable, audit-ready output
Cost ↓
Lower man-hours, fewer rework cycles
§ 04 · Real Drawings
Built on the documents your engineers actually ship.
P&IDs, airflow schematics, ceiling layouts, point-of-use diagrams — Flux ingests them at full fidelity, then automates validation, BOM extraction and compliance scoring.
Validation01 / 04
AHU-G01 — Schematic Airflow Diagram
HVAC · 15,600 CFM · Multi Dosage Facility
Tag Cross-Ref02 / 04
P&ID — Potable Water (Sheet 3 of 6)
Utilities · Oncology OSD & Sterile Formulation
BOM03 / 04
Point of Use Layout
Service distribution · clean utilities
Compliance04 / 04
Ceiling Finish Layout
Architectural · GMP zoning
Symbols detected
Pumps · valves · dampers · diffusers · sensors
Tags cross-referenced
Pipe IDs · room numbers · equipment codes
Compliance scored
WHO GMP · EU Annex 1 · FDA 21 CFR · ICH Q7
§ 05 · Architecture
Five layers. One platform.
Each layer is replaceable. Each layer is observable. Each layer is deployable on its own — a modular, cloud-native architecture built for pharmaceutical-grade reliability.
GPT-4oGeminiClaudeSupabaseRechartsTanStack
01 / 05
A
Input
Contracts · drawings · invoices · vendor submissions · compliance files
02 / 05
B
AI Processing
OCR + LLM · classification · context-aware extraction · RAG knowledge base
03 / 05
C
Intelligence
Vendor scoring · cost comparison · risk analysis · recommendations
04 / 05
D
Workflow
RFQ flows · approval chains · exception handling · notifications
05 / 05
E
Governance
Full traceability · audit logs · reference mapping · audit-ready output
§ 06 · Core Modules
Six intelligent hubs.
Each hub is a self-contained AI workflow engine with specialised knowledge, prompts and output formats — built for engineering teams who can't wait.
11 use cases01
6 use cases02RFI / RFP / Tenders Hub
AI-powered proposal automation. RFP summarise, auto-draft, RAG Q&A bot.
5 use cases03Vendor Intelligence
Vendor proposal analytics & scoring. 3-vendor compare, compliance score, risk flags.
4 use cases04BOQ Analysis
Quantity & cost intelligence. Item extraction, cross-compare, anomaly detection.
8 use cases05Deliverables Generator
Generate Pharma EPC deliverables register from SOW across Process, Mechanical, Electrical, Utilities & Validation.
7 use cases06Knowledge Bank
Project-grounded RAG over GMP/FDA/EU regulations & internal SOPs. Cited answers from your standards.
§ 07 · Agents
Autonomous workers, collaborating.
Flux agents read, decide and act across your operational stack — coordinating with humans at every approval boundary. Specialist agents handle ingestion, retrieval, comparison, validation and generation, all under one governance plane.
Multi-agent orchestration
Human-in-the-loop
Tool calling & MCP
Policy guardrails
Source-cited output
Replayable execution
§ 08 · Compliance
Pharma-grade by default.
Every Flux output ships with citations, lineage and an audit trail — ready for regulator review.
WHO GMPEU Annex 1FDA 21 CFR Part 11ICH Q7ASHRAENBCISO 14644GDPRSOC2-aligned
§ 09 · Specs
Enterprise essentials.
DeploymentSaaS · Private cloud · Hybrid
ModelsGPT-4o · Claude · Gemini · BYO
IngestionPDF · DWG · DXF · XLSX · DOCX · scanned
RetrievalHybrid RAG · semantic + lexical · citations
IdentitySSO · SCIM · role-based access
GovernanceG-Fence · PII redaction · audit logs
Data residencyEU · US · UAE · India · APAC
Training policyYour data never trains foundation models
§ 10 · FAQ
Frequently asked questions.
What is Flux AI?+
Flux AI is a modular, AI operating layer purpose-built for EPC firms — six intelligent hubs that read, validate and act on engineering drawings, tenders, vendor proposals, BOQs and compliance documents in real time.
Is it GMP / FDA compliant?+
Yes. Flux is built pharma-grade — outputs are audit-ready, cited against your standards (WHO GMP, EU Annex 1, FDA 21 CFR, ICH Q7), with full lineage on every answer.
Can we start with one hub?+
Yes. Most customers begin with a single hub (commonly Drawing Hub or Tenders Hub) on a 30-day pilot, then expand module-by-module.
How is Flux different from a generic LLM copilot?+
Generic copilots answer from public training data. Flux is grounded in your engineering standards, drawings and project history — every output cites its source and clears your approval workflow.
Where does our data live?+
Flux can be deployed on managed cloud or your private cloud. Your prompts, drawings and project data never train third-party foundation models.
§ 11 · Next Step
Pick a document-heavy workflow. We'll show it running in 30 days.
01
Pilot
one workflow, one BU, three milestones
02
Measure
cycle time, accuracy, traceability vs baseline
03
Scale
module-by-module across the platform