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Production AI Engineering in Action.

A detailed breakdown of our AI system builds, architecture decisions, real-world performance metrics, and verified client proof points.

Production Build Showcase
BUILD 01 // RAG & KNOWLEDGE ASSISTANTSInternal Platform // Dyta Engine

Enterprise Knowledge & RAG Assistant Platform

// DATA_PIPELINE_SEQUENCE
1. Client Prompt Payload2. PII Data Filter & Masking3. Qdrant Hybrid Vector Search4. Cross-Encoder Reranker5. Stream Response (<400ms)

Challenge

500+ unorganized technical documents and internal manuals causing high latency in engineering onboarding and customer support responses.

Engineering Solution

Built a custom, model-agnostic RAG engine featuring hybrid vector/keyword search, role-based access controls, and automated document ingestion pipelines.

Security & Compliance Posture

Built with zero third-party model training, PII filtering, strict role-based access control (RBAC), and isolated vector database namespaces.

Verified Performance Metrics

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

Technology Stack

AstroPythonFastAPIQdrantVercel AI SDK
BUILD 02 // WORKFLOW AUTOMATION & AGENTSFinTech & Accounting Ops Client

Autonomous Invoice & Document Extraction Pipeline

// DATA_PIPELINE_SEQUENCE
1. PDF Webhook Upload2. PII Redaction Engine3. LangGraph Extraction Agent4. Schema Validator5. ERP Database Sync

Challenge

Manual entry of 2,500+ complex multi-page PDF invoices monthly leading to error rates and 72-hour processing backlogs.

Engineering Solution

Engineered a multi-agent LangGraph pipeline with specialized OCR extraction, schema validation, and ERP webhook sync.

Security & Compliance Posture

SOC2-compliant staging environment, automated PII redaction, and encrypted audit logging.

Verified Performance Metrics

Processing Speed
12 sec
Per complex document
Extraction Accuracy
99.4%
Verified against human audit
OpEx Reduction
70%
Operational cost savings

Technology Stack

PythonLangGraphClaude 3.5 SonnetPostgreSQLDocker
BUILD 03 // CUSTOM MCP & INTEGRATIONHealthcare & Legacy Software Partner

Multi-Tool MCP Server for Enterprise Systems

// DATA_PIPELINE_SEQUENCE
1. LLM Tool Call2. OAuth2 Auth Handshake3. MCP Microservice Interceptor4. SQL Database Query5. Encrypted Payload Return

Challenge

Siloed database systems preventing AI assistant tools from accessing patient scheduling and records safely.

Engineering Solution

Developed a custom Model Context Protocol (MCP) server connecting LLM agents directly to SQL databases with granular permissions.

Security & Compliance Posture

HIPAA-ready boundaries, OAuth2 authentication, and isolated database query execution sandbox.

Verified Performance Metrics

API Latency
< 150ms
MCP tool execution time
Data Scope
100%
Fully isolated database sandbox
Downtime
0 hours
Zero legacy API disruption

Technology Stack

Node.jsTypeScriptMCP ProtocolASP.NET CoreSQL Server
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 engineer a production AI build for your business?

We build custom, model-agnostic AI systems with 100% IP ownership. From strategy and architecture to production code and handoff.