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AI Engineering & Software Integrations

We integrate practical, high-impact machine learning and LLM capabilities directly into your production software—enhancing user workflows, automating manual data processing, and enabling intelligent decision support.

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Applied Intelligence

Pragmatic AI Solutions That Deliver Measurable Business ROI

We focus on enterprise utility rather than experimental gimmicks. From document extraction and automated customer query routing to Retrieval-Augmented Generation (RAG) over private internal knowledge bases, we integrate AI securely without risking data leakage.

Strict Data Privacy

Zero data retention pipelines ensuring your company data is never trained upon.

Low-Latency Vector RAG

Embeddings caching, streaming HTTP responses, and semantic deduplication.

Consult AI Architecture Advisors

Zero Model Training Overhang

https://code4utech.com/services/ai-development

RAG Active

Enterprise Machine Intelligence Capabilities

Private RAG

Secure document query over proprietary PDF and ERP knowledge bases.

OCR Extraction

Automated invoice, PO, and receipt OCR with structured JSON verification.

Agent Workflows

Multi-agent execution for automated triage, dispatch, and reconciliation.

Churn Prediction

Statistical ML models identifying at-risk customer accounts early.

Guardrails

Deterministic Pydantic schema validation preventing hallucinations.

Architectural Scope

Applied AI Software Archetypes

Production implementations designed for reliability, deterministic outputs, and auditability.

Private RAG Knowledge Bases

Enable internal staff to query hundreds of standard operating procedures, contracts, and engineering handbooks with cited source references.

Exact Source Citations

Intelligent Document Pipelines

Transform unstructured scanned PDFs, purchase orders, and tax documents into validated, structured JSON directly injected into ERP databases.

Validated JSON Ingestion

Automated Decision Agents

Deterministic multi-agent workflows executing multi-step business tasks (e.g. cross-checking inventory, validating supplier quotes, notifying managers).

Deterministic Multi-Step Tasks

Technology Mastery

AI & ML Toolchain

Engineered with high-reliability machine intelligence frameworks.

Python & FastAPI

AI Microservices

LangChain & Llama

Orchestration

pgvector / Pinecone

Vector Embeddings

OpenAI & Anthropic

Zero Retention APIs

Redis Semantic Cache

Token Cost Reduction

Docker & AWS Sage

Cloud Serving

AI Lifecycle

Our AI Engineering Methodology

A disciplined framework delivering deterministic, accurate, and cost-controlled AI software.

Feasibility Assessment

Auditing data quality, evaluation metrics, token budget economics, and target accuracy thresholds.

Data Pipeline & Chunking

Cleaning, tokenizing, and chunking documents with contextual metadata extraction.

Vector Index Setup

Generating high-dimensional embeddings and indexing in pgvector/Pinecone with hybrid search.

Prompt & Guardrails

Few-shot prompt templates, output schema constraints (Pydantic), and hallucination defenses.

Integration & Streaming

Wiring AI microservices into your web/mobile frontend using streaming Server-Sent Events (SSE).

Eval & Benchmark Pass

Ragas / TruLens automated evaluation of retrieval precision, answer relevancy, and toxicity.

Production Cutover

Setting up rate limiters, fallback models, usage alerting, and zero-data-retention lock-in.

Cost & Quality Scaling

Semantic caching optimization, smaller fine-tuned model migrations, and token cost governance.

Applied AI & Automation Proofs

Explore how our engineering teams integrate intelligence into production systems.

View all case studies

Smart Invoicing Automation

BillVeda: Automated GST Parsing Engine

Cloud-based invoicing system automating multi-state GST tax rules, line-item parsing, and instant invoice PDF generation.

Read Case Study FinTech Web

Enterprise Security Intelligence

AuraLock: Anomaly Detection & Access Vault

Zero-knowledge encrypted credential vault with automated session risk scoring and role-based anomaly access monitoring.

Read Case Study Security Vault

Got Questions?

AI Integration FAQs

Pragmatic answers on privacy, hallucination mitigation, and ongoing token costs.

Will our confidential business data be used to train AI models?

No. We exclusively utilize enterprise commercial APIs (such as OpenAI Enterprise, Anthropic Commercial, and AWS Bedrock) that legally bind the provider to zero data retention and guarantee that customer prompts and outputs are never stored or used to train any model.

How do you prevent hallucinations in business software?

We constrain LLMs using strict Retrieval-Augmented Generation (RAG). The model is provided only with your verified source documents as ground truth and instructed to respond with exact citations or report when the information is not present. Outputs are validated using strict JSON schema parsers (Pydantic / Zod) before reaching your database.