Dawa
Financial Services · Investment Operations Software
Adding production AI around a regulated investment platform without replacing its .NET core
Dawa already operated as a private-equity and investment-placement platform built around an existing .NET and SQL Server core. Datics added AI and automation through services around that system, allowing document, onboarding and compliance workflows to evolve without replacing the regulated application underneath them.
The starting point
The platform already managed investor onboarding, deal rooms, valuation checks, due-diligence workflows and regulated investment operations.
What had to change
The product needed AI-assisted document intelligence, workflow automation and stronger support around onboarding, valuation and due diligence.
What couldn't break
The existing .NET application remained the regulated core. AML/KYC controls, permissions, document workflows and established operating processes had to stay intact.
Why this was hard
AI had to work through regulatory and approval boundaries rather than bypass them, while integrating cleanly with an application that was never designed around modern AI services.
What Datics changed
Datics created AI and automation services around the existing application instead of embedding a new architecture into the core. Python services could support document processing, investment workflows and external KYC/OCR integrations while the established .NET system continued governing the product.
Due-diligence intelligence
Support document-heavy review workflows.
Investor onboarding
Add automation around onboarding and placement operations.
OCR & KYC processing
Connect document extraction and identity/compliance services.
AI services around the core
Extend the product through Python services without replacing .NET.
Platform in action
Deal & Due Diligence
Where deal material and review workflows are managed.
Investor Onboarding
Where investors are onboarded into placements and operations.
Compliance & Documents
Where document handling meets AML/KYC controls.
What changed
AI and automation could evolve around the existing regulated application while the product's core workflows and controls stayed in place.
- Existing core
- .NET application retained
- AI delivery model
- Python microservices around the core
- Regulated controls
- AML/KYC and regulated workflows preserved
Under the hood
- Datics role
- AI and platform engineering alongside the existing regulated product.
- Integrations
- OCR and KYC providers, plus the platform's existing deal and onboarding services.
- Deployment
- AWS, alongside the existing .NET and SQL Server application.
- Production boundary
- Regulated investment platform with AML/KYC controls.
Technology
What this unlocked
The service boundary around the existing core creates a place where further AI capabilities can be introduced without turning each new feature into a modernization project.
Related work
COSMIC MarketVerse AI
Financial Services · Market Intelligence / Decision Support
Turning complex market data into an AI decision-support product
Financial-market data, company intelligence and agentic analysis brought into one decision-support experience.
Peret
Financial Services · Prediction-Market Analytics
Finding prediction-market mispricing with research-grounded AI forecasts
Research-grounded AI probabilities compared directly with live Kalshi and Polymarket pricing.
Peerlogic
Dental & Veterinary · Practice Communications SaaS
AI communication intelligence inside a live practice platform
AI communication and booking inside an established dental and veterinary practice platform.
Have a product with the same kind of constraints?
Tell us what already exists and what you want it to do. We will tell you what it takes.