Custom AI Development Services
Tailored AI solutions built around your business, your data, and your workflows.
We build production AI — RAG systems, custom chatbots, and LLM integrations that work on your real data and ship inside your real product. Not demos. Not experiments. Software.
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Your data, answered — RAG systems grounded in your documents, not hallucinating
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Production engineering — evaluation, monitoring, and cost control built in
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Model-agnostic — OpenAI, Claude, or open-source — whatever fits the job
TechnoBlick is a custom AI development company building LLM-powered products for businesses that need AI to actually work — not a demo that impresses in a meeting and fails on real questions. Whether you're looking to hire AI developers to add a chatbot to your product, build a RAG system over your company knowledge, integrate LLMs into an existing platform, or develop an AI product from scratch, we handle the full lifecycle: scoping, data pipelines, model selection, development, evaluation, and deployment.
What makes us different from AI consultancies is the same thing that runs through everything we do: we're product engineers. An AI feature is 20% model and 80% software — data ingestion, retrieval quality, prompt architecture, guardrails, latency, cost management, and the UI it lives in. We build all of it, on the same stacks that power our web and app work, so your AI ships as part of your product instead of bolted onto it.
OUR SERVICES
What we build
RAG systems (Retrieval-Augmented Generation)
Build AI that answers from your own knowledge base instead of hallucinating. We develop production-ready RAG systems with document ingestion, chunking, embeddings, vector databases, retrieval optimization, and citation-backed responses that your team and customers can trust.
Custom AI chatbots & assistants
Create intelligent assistants for customer support, sales, and internal teams. We deploy AI chatbots across your website, app, Slack, or WhatsApp with conversation memory, human handoff, analytics, and knowledge tailored to your business.
LLM integration into existing products
Add AI capabilities to your existing software, SaaS platform, or internal tools. From summarization and semantic search to content generation and data extraction, we integrate leading models while handling rate limits, caching, fallbacks, security, and cost optimization behind the scenes.
AI product development
Turn AI product ideas into production-ready applications. We design the architecture, select the right models, build scalable applications, and iterate from MVP to launch with a practical, engineering-led development process.
Document intelligence & automation
Extract structured information from invoices, contracts, forms, reports, and other business documents using AI-powered processing. Automate repetitive document workflows while improving accuracy and reducing manual effort.
Evaluation, safety & optimization
Production AI requires more than great prompts. We build evaluation frameworks, reduce hallucinations, implement guardrails, defend against prompt injection, optimize latency, and significantly reduce AI operating costs through intelligent routing, caching, and model selection.
Our AI Stack
We are model-agnostic and infrastructure-flexible. We build with the tools that best balance performance, cost, and data privacy for your specific use case.
Models
OpenAI (GPT-4 family), Anthropic Claude, Google Gemini, and open-source models (Llama, Mistral) where data control or cost demands it — we route to what fits.
Frameworks & Retrieval
LangChain, LlamaIndex, custom pipelines; vector databases including Pinecone, pgvector, and Qdrant.
Application Layer
Next.js, Node.js, Python, Laravel — the exact same robust production stacks we use for the rest of our enterprise engineering.
Deployment
Your cloud or ours — delivered with comprehensive monitoring, logging, and cost dashboards from day one.
The Baseline
What every engagement includes
These aren't upsells. They're the baseline on every project we ship, big or small.
Feasibility verdict first
an honest go-or-no-go assessment before you invest in development
Evaluation harness
AI quality measured objectively against your real data and business use cases
Guardrails & safety engineering
hallucination controls, prompt injection defenses, and clearly defined AI boundaries
Cost engineering
caching, intelligent routing, and model optimization to reduce long-term AI costs
Full documentation & ownership
your code, prompts, pipelines, and evaluation framework remain fully yours
30 days post-launch support
launch support included, with optional retainers for continuous optimization and improvements
What drives the cost of custom AI development?
Three factors: integration depth (adding an LLM feature to an existing product sits at the lower end), data complexity (RAG over large, messy document sets costs more than clean ones), and product scope (AI-first builds are scoped like any software project). The second budget most vendors hide: ongoing model/API running costs — we estimate them in discovery and engineer them down. Every quote is fixed after the feasibility phase."
Foundation
per project/month
Growth
per project/month
Enterprise
per project/month
Our Process
We don't do guessing games. Every campaign follows a strict, engineering-grade rollout schedule. Here is exactly what happens when you sign.
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Discovery & feasibility
What should AI do for you, what data exists, what accuracy is achievable, what it will cost to run. Including the honest answer when the right call is "don't build this."
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Prototype & evaluate
A working prototype on your real data, plus an evaluation harness that measures quality objectively — so decisions are made on evidence, not vibes.
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Build
Production engineering: pipelines, guardrails, UI, integrations, and testing. Weekly demos as always.
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Deploy & tune
Launch with monitoring, then iterate on real usage: retrieval tuning, prompt refinement, cost optimization.
Why teams pick TechnoBlick for AI development
Production over demos
Anyone can build an impressive AI demo. We build production-ready systems that handle real users, edge cases, security, monitoring, and operating costs—not just a prototype that works on stage.
Honest feasibility calls
Not every problem needs AI. We assess your idea, available data, and expected ROI before development begins, and we'll tell you when a simpler solution is the better business decision.
Full product team
AI engineers, backend developers, frontend developers, and designers work together under one roof. Your AI feature ships with the interfaces, APIs, integrations, and infrastructure required for real-world deployment.
You own everything
Every deliverable belongs to you—from source code and prompts to evaluation suites, data pipelines, and documentation. No vendor lock-in, no hidden dependencies, and complete control over your AI platform.
AI Development FAQs
Common Questions
Cost & getting started
Pricing depends on what you're building. Adding an AI feature to an existing product sits at the lower end, while production-grade RAG systems and AI-first applications require a larger investment. We also estimate ongoing model and API costs during discovery and design the solution to keep long-term operating expenses under control through caching, routing, and model optimization. Fixed project quotes are provided after the feasibility assessment. Book a free feasibility call.
Technology, accuracy & security
Retrieval-Augmented Generation (RAG) allows an AI system to answer questions using your own documents, policies, product information, or knowledge base instead of relying solely on its general training. If you need AI that provides accurate, business-specific answers with supporting sources, a RAG system is usually the right approach.
AI models can generate inaccurate information if left unmanaged. We reduce that risk by grounding responses in your data, requiring citations where appropriate, implementing confidence thresholds, adding guardrails, and continuously evaluating accuracy with automated testing. Managing hallucinations is a core part of production AI engineering.
Yes. Most business AI solutions retrieve information from your data rather than training models on it, which is both more secure and more cost-effective. Your data remains under your control, access is restricted, and for organizations with strict security requirements, we can deploy open-source AI models entirely within your own infrastructure.
There isn't a universal winner. Different models excel at reasoning, writing quality, speed, context size, cost, and deployment flexibility. We're model-agnostic and select the best option for each use case, often combining multiple models within a single solution to achieve the best performance and cost efficiency.
Working with us
Absolutely. This is one of our most common projects. We integrate AI capabilities directly into your existing application, APIs, or workflows without requiring you to rebuild your entire product from scratch.
Yes. We develop autonomous AI systems that can reason, make decisions, and complete multi-step workflows through our Agentic AI Development service. If you need AI that answers questions, this service is the right fit. If you need AI that performs tasks autonomously, our Agentic AI service is the better choice.
Have an AI use case — or wondering if you do?
We offer a range of services to help you achieve your goals. Explore our related services below to find the perfect fit for your needs.