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AI Solutions and Development
GLAD Studio engineers custom AI solutions that connect frontier language models with proprietary business data, APIs, and operational workflows. We build production-ready LLM applications, RAG search pipelines, autonomous AI agents, and computer vision systems backed by deterministic guardrails and cost-optimized routing.
Production AI Systems Engineered for Real-World Demands
We design and implement AI applications that solve specific operational challenges, automate repetitive human tasks, and unlock insights from unstructured corporate data.
Custom LLM Applications
Context-aware applications powered by frontier and open-source language models tailored to your domain-specific data and business logic.
- Structured JSON extraction from unstructured text
- Interactive conversational assessment & coaching platforms
- Cost-aware model routing (GPT-4o, Claude 3.5, Llama 3)
- Strict evaluation guardrails & latency monitoring
Autonomous & Supervised AI Agents
Multi-agent systems engineered with LangGraph and CrewAI that plan tasks, invoke external API tools, query databases, and execute operational workflows.
- Stateful agent loops with human-in-the-loop approvals
- Dynamic tool calling & external API orchestration
- Self-correcting code and query execution sandboxes
- Deterministic fallback paths for mission-critical operations
Retrieval-Augmented Generation (RAG)
Enterprise search and knowledge retrieval engines that ground model responses in your proprietary PDFs, databases, and customer records with zero hallucination.
- Hierarchical document chunking & semantic embeddings
- pgvector & hybrid dense/sparse vector search
- Context compression & reciprocal rank fusion (RRF)
- Source citation attribution for auditable outputs
Computer Vision & Media Intelligence
Visual intelligence pipelines that process imagery and video streams for automated classification, OCR extraction, and anomaly detection.
- Document OCR & unstructured invoice parsing
- Automated image classification & tagging pipelines
- Media integrity validation & deepfake detection
- Real-time visual quality inspection
Enterprise AI Engineering Foundations
Deploying AI models to production requires rigorous guardrails, deterministic data contracts, and enterprise security standards.
Vector Data & Retrieval Layer
High-dimensional vector storage built on pgvector, Pinecone, or Qdrant with hybrid keyword/semantic search, metadata filtering, and automated embedding updates.
Guardrails & Privacy Isolation
Zero data-retention policies, PII anonymization layers, regex-based prompt sanitization, and output schema validation using Pydantic.
Model Cost & Latency Routing
Intelligent gateway routing that dispatches simple tasks to lightweight models and complex reasoning to frontier models, cutting token expenses by up to 70%.
Observability & Evals Framework
Continuous logging of prompt tokens, model latency, retrieval recall scores, and automated synthetic evaluation suites against test datasets.
Our 4-Stage AI Engineering Process
We apply systematic software engineering principles to AI development, validating model accuracy and data grounding at every stage.
Feasibility Spike & Data Audit
We inspect your unstructured data assets, evaluate token economics, and validate technical viability with a rapid proof-of-concept benchmark.
Pipeline Architecture & Evaluation Setup
We design the RAG or agent architecture, establish baseline evaluation criteria, and implement semantic chunking and embedding strategies.
Model Integration & Tool Grounding
We engineer custom FastAPI microservices, connect agent tool definitions, configure pgvector storage, and enforce Pydantic output schemas.
Hardening, Guardrails & Production Launch
We run vulnerability scans, configure token caching and fallback handlers, and deploy containerized services with real-time latency monitoring.
Real AI Projects Built by GLAD Studio
AI Mock Interview Platform
Real-time conversational AI system conducting dynamic technical interviews, transcribing speech in low-latency streams, and producing structured evaluation scores.
Lead Enrichment Pipeline
High-throughput automated lead sourcing and cleansing pipeline leveraging LLM extraction to parse company websites, verify contacts, and enrich CRM profiles.
Fluxor File Intelligence
Desktop application analyzing local document content and metadata using machine learning models to automatically suggest smart folder hierarchies and renames.
Connected Engineering Capabilities
AI Solutions & Engineering Q&A
Direct, factual answers to key questions about building AI solutions with GLAD Studio.
AI Engineering Insights & Architecture Guides
Explore in-depth engineering breakdowns, cost analyses, and architectural decision frameworks authored by the GLAD Studio engineering team.
AI Development Cost in India: 2026 Practical Pricing Guide
Understand project complexity tiers, vector database infrastructure costs, model token fees, and engineering budgets.
What Is AI Agent Development? Practical Guide for Businesses
A deep dive into tool calling, LangGraph stateful loops, memory systems, and production safety guardrails.
RAG vs Fine-Tuning: Which AI Approach Should Your Business Use?
Compare dynamic pgvector knowledge retrieval against fine-tuning model weights for formatting, syntax, and tone.
Let's Engineer Your AI Solution
From RAG pipelines and custom AI agents to LLM-powered applications, partner with GLAD Studio for robust, secure, and production-ready artificial intelligence engineering.