Skip to content
ddyta.ai
~/dyta.ai/solutions/fintech-ai

Autonomous Audit Pipelines & Financial RAG Systems.

Engineered for financial institutions requiring sub-second document search, automated audit trail generation, and strict data privacy boundaries.

TARGET OUTCOME

"Sub-400ms retrieval across 500k+ financial records with zero third-party model training."

Discuss Your Project →
Industry Bottlenecks Solved

Unstructured Financial Filings

Analysts spending 40% of their workday reading 10-K filings, loan agreements, and audit reports to find risk clauses.

Model Training & Privacy Risks

Strict regulatory requirements prohibiting proprietary financial data from training public LLM models.

Rigid Legacy Banking Cores

Inability to integrate AI features into legacy banking software without breaking compliance audits.

Engineering Architecture

Hybrid Vector Search RAG Engine + PII Masking

Dense + Sparse hybrid vector retrieval with automated PII masking and zero data retention endpoints.

// EXECUTION_PIPELINE_SEQUENCE
1. Financial Query Payload2. Automated PII Masking3. Qdrant Hybrid Vector Search4. Cross-Encoder Reranker5. Stream Response (<400ms)

Verified ROI Metrics

Query Latency
< 400ms
Sub-second response
Search Efficiency
+85%
Faster document retrieval
Data Privacy
100%
Zero 3rd-party model training

Technology Stack

AstroFastAPIQdrantBM25 RerankerPostgreSQLOpenAI Enterprise
Executive Risk Clearance

Solving silent objections before code is written.

Production AI projects fail when security, legacy integration, or vendor lock-in are ignored. Here is how we guarantee safety across every build.

DATA PRIVACY

"Will our proprietary data or IP train third-party public AI models?"

✓ Zero Third-Party Training Guaranteed.

We enforce enterprise zero-retention API endpoints, isolated vector database namespaces, and automated PII data masking before any prompt payload reaches an LLM model.

TECH DEBT & INTEGRATION

"Will an AI build require rewriting our existing software stack?"

✓ Decoupled Architecture & Retrofits.

We build AI middleware microservices and custom Model Context Protocol (MCP) servers that plug into your existing ASP.NET, Node, Python, or SQL databases via REST/gRPC without touching legacy core code.

IP OWNERSHIP & HANDOFF

"What happens to the code, models, and docs when your team leaves?"

✓ 100% Client IP Handoff & Independence.

All source code, fine-tuned model weights, prompt engineering suites, CI/CD pipelines, and architectural docs transfer directly to your GitHub/cloud tenant. Your team maintains total long-term independence.

Verified Client Outcomes

What engineering leaders say about our builds.

Direct feedback from CTOs, Founders, and VPs of Operations who partnered with dyta.ai for production AI systems.

RAG & KNOWLEDGE ASSISTANT< 400ms Latency

"dyta.ai reduced our internal technical document search overhead from 45 minutes to sub-400ms retrieval while guaranteeing zero third-party model training on our proprietary IP."

VP of Operations

Mid-Market Logistics & Supply Chain

AI AGENT AUTOMATION+85% Ops Efficiency

"They delivered a complete LangGraph agent automation suite in 3 weeks, transferred 100% of the source code and evaluation suites, and enabled our team to extend it independently."

Founder & Lead Architect

B2B SaaS Platform

CUSTOM MCP & INTEGRATION0 Legacy Disruptions

"The custom Model Context Protocol (MCP) server retrofitted our legacy SQL database without disrupting a single existing API endpoint. Outstanding senior engineering quality."

VP of Engineering

Enterprise Financial Services

Ready to build an AI solution for FinTech & Financial Services?

Our team can design, scope, and engineer custom AI software with 100% IP ownership.

Discuss Your Project →