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Production AI & LLM Engineering
Available for Q3/Q4 AI Sprints

Integrate Production-Grade AI & LLM Workflows into Your Software.

Move beyond toy chatbots. I engineer deterministic generative AI pipelines, multimodal document ingestion, type-safe Zod schemas, and streaming UIs with Gemini 1.5, OpenAI GPT-4o, Vercel AI SDK, and semantic caching.

Output Reliability
100% Zod Type-Safe
Cost Control
Semantic Vector Caching
Data Privacy
Zero-Retention Enterprise
Turnaround
2–3 Weeks Delivery
Target Fit

Who This AI Service Is Engineered For

Whether you are embedding AI into an existing platform or building a completely new AI-driven product, here is how we deliver immediate leverage.

AI Feature Integration

SaaS & Product Companies

You want to launch intelligent AI copilot features, automated generative workflows, or smart search inside your existing web product without hallucination risks.

Key Objectives:
Vercel AI SDK low-latency streaming
Type-safe JSON schema enforcement
Semantic vector search & RAG pipelines
Process Automation

Operation-Heavy Businesses

Your team drowns in manual document review, invoice data entry, PDF parsing, or repetitive categorization and needs automated multimodal pipelines.

Key Objectives:
Multimodal PDF, image & invoice intake
80% reduction in manual data processing
Automated database & webhook dispatch
AI-First Products

AI Startup Founders

You are launching an AI-first SaaS product and need senior engineering to build the end-to-end architecture, prompt guardrails, and token cost budgeting.

Key Objectives:
Cost-controlled semantic caching
Multi-step autonomous agent workflows
Production cloud deployment & rate limits
Full-Scope Deliverables

What You Get: Production-Grade AI Engineering

Everything required to ship robust, type-safe, cost-controlled generative AI features without fragile prompt wrappers.

01

Deterministic Structured Schema Pipelines

Zero-hallucination guarantees using Zod schema validation and LLM function calling to output 100% type-safe JSON records ready for database storage.

Zod ValidationFunction CallingType SafetyZero Hallucination
02

Multimodal Document & Vision Ingestion

Automated extraction engines parsing messy multi-page PDFs, invoices, property inspection photos, and medical intake records using Gemini 1.5 & GPT-4o.

Gemini 1.5 ProGPT-4o VisionPDF ExtractionOCR Automation
03

Sub-Second Streaming UI with Vercel AI SDK

Low-latency streaming text generation, progressive UI rendering, and bidirectional tool execution integrated seamlessly with Next.js App Router.

Vercel AI SDKStreaming UIGenerative WidgetsNext.js
04

Vector Search & Retrieval-Augmented Generation (RAG)

Contextual knowledge retrieval using Supabase Vector and PGVector to inject accurate, up-to-date company documentation into model reasoning loops.

PGVectorSupabase VectorEmbeddingsHybrid Search
05

Semantic Caching & Token Cost Optimization

Multi-tiered caching layers and dynamic model routing that reduce monthly OpenAI/Gemini API expenses by up to 60% while speeding up response times.

Semantic CachingCost OptimizationModel RoutingRate Limiting
06

Enterprise Data Privacy & Security Guardrails

Zero-retention enterprise routing, input sanitization, PII redaction, and prompt injection defense ensuring proprietary company data remains protected.

Zero-RetentionPII RedactionPrompt DefenseEnterprise Security
Strategic Comparison

Why Hire a Dedicated AI Specialist?

Compare dedicated AI engineering versus generic web agencies or fragile no-code AI builders.

Evaluation Criteria⭐ Satish Patil (AI Specialist)Generic Web AgencyNo-Code / Cheap AI BotFull-Time AI Hire
AI Output Reliability100% Type-Safe Zod SchemasUnstructured Raw Text (Fragile)Basic OpenAI Zapier / Make WrappersRequires Specialized AI Engineer
Token Cost ControlSemantic Caching & Prompt CompactionUncontrolled Monthly API OverrunsZero Cost Caching MechanismsOngoing Maintenance Overhead
Streaming User ExperienceSub-Second Vercel AI SDK Streams10s Frozen Screen Wait TimesSlow Third-Party API WebhooksRequires Frontend SDK Expertise
Data Privacy & ComplianceZero-Data Retention Enterprise APIGeneric Shared EndpointsPublic Automation Cloud ExposureCompliance Engineering Needed
Delivery Timeline2 to 3 Weeks Turnkey Deployment2 to 4 Months Bureaucracy1 Week (Breaks Immediately)3+ Months Recruiting Lag
Working Model

Structured 4-Step AI Pipeline Process

From schema boundary definitions to multimodal ingestion, streaming UI integration, and semantic caching.

STAGE 01Days 1–3

Data Audit & Schema Boundary Design

We analyze your document/data inputs, define strict Zod output schemas, establish prompt boundary rules, and select cost-optimal models.

STAGE 02Week 1

Multimodal & Retrieval Pipeline Build

Engineering automated ingestion pipelines for PDFs, images, or tabular data, paired with vector embeddings and semantic context retrieval.

STAGE 03Week 2

Streaming UI & Tool Integration

Connecting the AI backend to your web application using Vercel AI SDK for instant text streaming, generative UI widgets, and bidirectional tool execution.

STAGE 04Week 3

Caching, Guardrails & Production Launch

Implementing semantic caching, token cost limiters, prompt injection guardrails, deploying to cloud infrastructure, and 30-day post-launch support.

Engagement Options

Structured Engagement Models

Choose the scope that matches your product requirements—from technical feasibility blueprints to turnkey AI deployment.

Technical Blueprint

AI Feasibility & Architecture Audit

For teams exploring AI integration who need a clear architecture plan, prompt design, and accurate token cost projection.

Included in Scope:
Data ingestion & pipeline feasibility audit
Deterministic Zod schema & prompt design
Model selection & monthly token cost forecast
RAG & vector database architecture plan
Security & zero-data-retention compliance review
Book AI Architecture Audit
Most Popular Build
Most Popular Engagement

Turnkey Production AI Pipeline

The complete 2–3 week build embedding production-grade AI, multimodal extraction, streaming UI, and cost caching into your product.

Included in Scope:
Gemini 1.5 Pro & OpenAI GPT-4o integrations
Strict Zod JSON Schema type validation
Multimodal PDF / image / invoice parsing
Vercel AI SDK low-latency streaming UI
Semantic caching reducing token costs up to 60%
Cloud deployment, rate limiters & security rules
100% full IP code ownership & 30-day hypercare
Discuss AI Pipeline Build
Complex Workflows

Custom Autonomous Agent Systems

For enterprises requiring multi-step autonomous agents, complex RAG architectures, and custom fine-tuning pipelines.

Included in Scope:
Everything in Turnkey AI Pipeline
Multi-step autonomous agent state machines
Advanced hybrid vector + keyword search RAG
Custom API tool calling & background cron automation
Dedicated weekly engineering sprint retainers
Priority 24/7 technical advisory support
Inquire Agentic Scope
Live Production Proof

Explore Real Automated AI Workflows I've Shipped

Automated Document Processing80% Time Cut

Enterprise Valuation CRM & Automated DOCX Report Generator

Engineered automated data extraction and multi-role inspection pipelines converting GPS, photos, and appraisal data into formatted bank reports in <3s.

Read Architectural Deep-Dive
Automated Medical Intakes70% Cost Cut

Telehealth Platform & Automated Clinical Workflows

Built sub-second clinical intake questionnaires with automated doctor review queues, structured data capture, and Stripe payment routing.

Read Architectural Deep-Dive
Commercial & Technical FAQs

Frequently Asked Questions

How do you guarantee that AI models will not hallucinate false information?

We implement strict programmatic schema enforcement using Zod type validation, OpenAI/Gemini function calling, and fallback repair loops. The model is restricted to outputting deterministic, type-safe JSON that is verified before entering your database.

How do you keep LLM API token costs predictable and manageable?

We implement multi-tiered semantic vector caching to serve repeat queries with zero API token spend, compress prompts systematically, and dynamically route simple tasks to fast, lightweight models while reserving heavy reasoning models for complex requests.

Can you process complex documents like multi-page PDFs, spreadsheets, and photos?

Yes. Leveraging Gemini 1.5 Pro and GPT-4o vision capabilities, we build end-to-end multimodal intake pipelines that parse invoices, medical intakes, handwritten notes, and property inspection photos into structured database records.

Can AI features be integrated into our existing application stack?

Yes. We build standalone AI microservices or modular API endpoints that seamlessly integrate with your existing Next.js, React, Node.js, Python, or Laravel codebases via standard REST and webhook interfaces.

Is our proprietary customer data kept private and secure?

Yes. All API integrations utilize enterprise endpoints with zero-data-retention agreements, ensuring your proprietary data is never stored by third-party providers or used to train public foundation models.

Ready to Build Your AI Pipeline?

Let's Engineer Production AI for Your Product

Book a free 30-minute discovery call to review your data workflows, explore multimodal extraction feasibility, and receive an exact fixed-timeline proposal.