Instant Visibility Into Every Document
See exactly where things stand at a glance. Track processing volume, approval rates, and bottlenecks in real time — no more chasing status updates across teams.
Precision at Scale. Intelligence at Work.
DIP enforces Document Intelligent Automation with Human Accountability.
- Multi-Cloud Ready
- Enterprise-Grade Security
- On-premise available
Built for Regulated Industries
- Banking & Finance
- Insurance & Brokerage
- Government
- Legal & Compliance
- Real Estate
- Automotive
- Pharmaceutical
- Healthcare
- Human Resources
An AI middleware layer, not a core replacement.
DIP sits between your document repositories and your transactional systems. Multi-provider AI (Azure, AWS, GCP) with automatic failover. Dual-engine OCR (LiteParse + Mistral). Continuous learning from analyst corrections. Connects to 7+ storage backends — Local, Azure Blob, S3, SFTP, Google Drive, OneDrive, Box.
Why DIP
What Changes When Documents Process Themselves
25s
Processing: 12 Min → 25 Seconds
Document processing time drops from 12 minutes of manual review to 20-25 seconds of AI-powered extraction and validation (measured in testing).
Features
Turn Documents Into Decisions — Faster
Stop losing hours to manual reviews. DIP reads, extracts, and validates your documents automatically so your team can focus on what actually moves the business forward.
Accurate Data From Any Document
Automatically pull the right fields from invoices, contracts, IDs, and 50+ document types. Pre-built for Banking, Real Estate, Automotive, Pharma, and more — ready to go on day one.
Read Every Document, Even the Messy Ones
Dual OCR engines work in parallel to capture text from scans, photos, and PDFs with best-in-class accuracy. See exactly what was extracted, right on the original document.
Catch Discrepancies Before They Cost You
Compare documents side by side in seconds. Four detection modes surface inconsistencies that manual reviewers miss — protecting your business from fraud and costly errors.
Ask Questions, Get Answers From Your Documents
Search by meaning, not just keywords. Ask anything across a single document, a full case file, or your entire document library — and get precise, sourced answers instantly.
Enterprise Security You Can Trust
Bank-grade encryption, role-based access control, and a complete audit trail for every action. Built from the ground up for regulated industries where compliance is non-negotiable.
Automate the Way You Work
Design custom workflows that route documents through approval chains, trigger notifications, and escalate exceptions — all without writing a single line of code. Your rules, your process, fully automated.
Modules
Everything You Need, All in One Platform
Seven integrated modules that eliminate tool sprawl and give your team a single place to process, analyze, and act on every document.
Smart Document Analysis
Let AI handle the routine decisions. Documents are automatically approved, flagged for review, or escalated — based on the confidence rules you set.
Security & Compliance
Built for Regulated Industries
Enterprise-grade security architecture designed to meet the strictest compliance requirements in banking, healthcare, government, and legal sectors.
SOC 2 Type II
Architecture designed for SOC 2 compliance. Formal audit planned for 2026.
GDPR Design Principles
Data subject rights, data minimization, and configurable retention policies built in. Formal certification pending.
HIPAA-Aligned Architecture
Technical safeguards for protected health information in place. BAA available on Enterprise plan.
ISO 27001 Framework
Security management practices following ISO 27001 controls. Certification in roadmap.
Role-Based Access Control
Granular RBAC with custom roles, permissions, and API key scopes per user and team.
Immutable Audit Trail
Every action logged with actor, timestamp, traceId, and idempotency key for full traceability.
Data Encryption
AES-256 encryption at rest and TLS 1.3 in transit. Zero plain-text document storage.
On-Premise Deployment
Full air-gapped deployment option. Your data never leaves your infrastructure.
DIP's security architecture is designed to support compliance in regulated industries. Formal certifications are in our 2026 roadmap.
Pricing
Tailored to Your Needs
Full platform for regulated industries with on-premise deployment.
- Multi-tenant workspaces with per-workspace encryption
- 50+ document types across 5 industry profiles
- On-premise / Kubernetes / multi-cloud deployment
- Visual Workflow Engine with 17 node types
- Multi-step review chains with 4-eyes & SLA escalation
- Skills Framework with tool calling & business profiles
- 70+ API endpoints, webhooks & MCP server
Contact
Get in Touch With Our Team
Ready to transform your document workflows? Our team is here to help you get started with DIP.
Headquarters:
400 N Ashley Dr. Suite 1900, Tampa, Florida 33602
Sales:
+1 786 567 3454
Email:
sales@getdip.ai
Support Hours:
Monday to Friday, 8 AM - 6 PM (ET)
FAQ
Frequently Asked Questions
DIP comes with 50+ pre-configured document types across 5 industry profiles (Banking, Brokerage, Real Estate, Automotive, Pharmaceutical). Each profile includes 10 document types, 3 specialized AI skills, and a pre-configured business profile. You can also generate custom document types automatically — upload a sample document and DIP's AI wizard creates the type definition and extraction prompt for you.
Every extracted field receives a confidence percentage validated through Zod schemas. You configure global and per-document-type thresholds that determine whether a document is auto-approved, sent for manual review, or rejected. This human-in-the-loop approach ensures quality while maximizing automation.
Yes. DIP provides a comprehensive REST API with segmented API keys supporting granular scopes (config.read, workflows.write, etc.). It also supports webhook notifications and can be deployed alongside your existing infrastructure via Docker Compose or cloud containers.
When analysts make corrections during manual review, DIP captures the exact changes and stores them as vector embeddings in PostgreSQL via pgvector. In future analyses of the same document type, this correction history is automatically injected as context, improving accuracy without retraining the base AI model.
Yes. DIP supports Docker Compose for self-hosted, Kubernetes with Helm charts and Argo CD for production (AKS, EKS, GKE, on-prem), and Azure Container Apps for demos (~$25/month). Cloud deployment on Azure, AWS and GCP. The architecture is model-agnostic, supporting hot-swap between Azure AI Foundry, OpenAI, Anthropic, AWS Bedrock and GCP Vertex AI — change providers from the UI without restart.
DIP is designed for any type of company handling at least 200 documents per day, that seeks to maintain full control of the platform—especially for regulatory compliance—and where security is a top priority.
Industry data shows manual invoice processing costs $12.40-$17.50 per document (Ardent Partners, 2024). For regulated industries, U.S. firms spent $81.87 billion on financial crime compliance in 2023 (LexisNexis), and global AML fines exceeded $4.3 billion (Fenergo, 2024). Automating document extraction and validation directly reduces these costs.
DIP is a middleware layer — it sits between your document repositories and core systems without replacing anything. Key differentiators: multi-provider AI with automatic failover (Azure, OpenAI, Anthropic, AWS Bedrock, GCP Vertex), dual-engine OCR with spatial PDF viewer, continuous learning from analyst corrections (memoryIdp), visual workflow engine with 17 node types, multi-step review chains with 4-eyes principle and SLA escalation, 7 storage backends, and on-premise deployment. Deploy in 1-3 days at $300-2,000/month — vs. $50K-$500K/year and 3-12 months for enterprise IDP.
Every extracted field has a confidence score. You set thresholds that determine auto-approval, manual review, or rejection. When analysts correct errors, DIP's memoryIdp system captures corrections as vector embeddings and uses them as context for future analyses — improving accuracy over time without retraining the base AI model.