AI Solutions for High-Growth Teams
LLMs integrated where they create real leverage — support automation, smart search, document workflows and assistants, with strict evaluation guardrails and cost-routing.
Enterprise RAG Search Pipelines
Hybrid dense-sparse vector retrieval over enterprise documents, databases, and knowledge bases using pgvector, Cohere reranking, and semantic chunking.
Autonomous Workflow & Task Agents
Multi-step AI agents equipped with deterministic function calling, state machine controllers, and automated human-in-the-loop escalation gates.
Conversational Voice & Chat Interfaces
Low-latency streaming voice and text conversational engines with websocket real-time audio parsing and custom persona prompt engineering.
Document Intelligence & Extraction
Automated OCR, unstructured invoice parsing, and contract entity extraction transforming scanned paperwork into validated JSON schemas.
Feasibility Audit & Data Architecture
Evaluating token economics, defining quantitative evaluation metrics, and architecting data ingestion pipelines with semantic chunking.
RAG Pipeline & Prompt Engineering
Implementing hybrid vector search, context window optimization, custom rerankers, and deterministic tool-calling schemas.
Guardrails & Automated Evaluation Suites
Building automated LLM evaluation harnesses, hallucination detectors, content safety moderation layers, and latency optimizations.
Production Infrastructure & Scaling
Deploying model caching with Redis, multi-provider token routing (OpenAI/Anthropic/Local LLMs), and continuous telemetry monitoring.
AI Development Cost in India: What Businesses Should Budget in 2026
A comprehensive guide to AI development costs in India. Learn the key cost drivers, architectural complexity tiers, infrastructure expenses, and how to budget for production AI systems.
RAG vs Fine-Tuning: Which Approach Is Right for Your AI Application?
Compare Retrieval-Augmented Generation (RAG) with LLM fine-tuning. Discover when to ground models on dynamic data versus adapting model behavior, tone, and domain syntax.
What Is AI Agent Development? A Practical Guide for Businesses
A deep dive into AI agent development for engineering leaders and founders. Explore agent loops, tool calling, memory management, orchestration frameworks, and production guardrails.
How to Build an AI Agent for Your Business in 2026
Step-by-step engineering guide to building a production AI agent. Learn workflow selection, tool definition, memory state management, deterministic guardrails, and evaluation frameworks.
Start your AI Solutions sprint this month.
Direct communication with senior engineers. Fixed weekly cadence, continuous staging demos, and complete IP transfer.
FAQ.
Clear Answers on Scope,
Timelines and Cost
Before Any Work
Begins जवाब.
Every project is custom-scoped based on your specific requirements, feature complexity, and timeline. We work on a transparent, fixed-price milestone basis — meaning after an initial discovery call, you receive a detailed proposal with a fixed quote and guaranteed delivery timeline before any code is written.
Most projects begin within 1–2 weeks of signing. For urgent work, we can sometimes start within a few days.
Yes — most of our clients are non-technical. We translate ideas into clear technical specifications, user-friendly designs, and shipped products, ensuring you always understand the trade-offs at every step.
You own 100% of all intellectual property, source code, designs, and project assets from day one. Upon final milestone completion, full repository access and credentials are handed over.
We work in structured 2-week sprints with weekly async updates, active messaging channels (Slack/Discord), and direct access to a live staging environment so you can test features as they are built.
Yes. Whether upgrading an existing application, refactoring legacy code, or integrating new AI features and third-party APIs, we can seamlessly audit and build directly within your current codebase.
We focus on modern, type-safe, and scalable web and mobile stacks — primarily React, Next.js, TanStack Start, TypeScript, Node.js, Python, Flutter, Tailwind CSS, and cloud platforms like AWS and Vercel.
We provide dedicated post-launch support for bug fixes, performance monitoring, and maintenance. Many of our clients continue working with us long-term as their dedicated development team.