◆ Generative AI Development Company

Build generative AI products that customers actually use

We help businesses design, develop and deploy custom generative AI — LLM apps, AI chatbots, RAG knowledge systems and AI agents — engineered for accuracy, security and real ROI. From first idea to a monitored production system.

4.9★★★★★
4.8★★★★★
5.0★★★★★
⚙️
250+AI & software projects delivered
📈
40%Avg. drop in manual effort after automation
3–6 wksFrom idea to a working AI prototype

Trusted by startups, scale-ups & enterprises worldwide

Solve real problems

Where generative AI moves the needle

Click a panel to see the business problem, how we solve it with generative AI, and the kind of results to expect.

01Support overload
Customer Support

Support teams drowning in repetitive tickets

Agents spend hours answering the same questions while customers wait, CSAT slips, and support costs climb with every new hire.

💡Our fix: An AI support assistant grounded in your help docs and order data — it resolves routine queries instantly and hands complex ones to a human with full context.
~55%tickets auto-resolved
24/7instant responses
+18%CSAT lift
02Content bottleneck
Content & Marketing

Content production can't keep up with demand

Product descriptions, blogs and campaign copy pile up. Manual writing is slow, inconsistent and expensive to scale.

💡Our fix: A brand-tuned generative content engine that drafts on-brand copy, SEO metadata and variants at scale — with human review built in.
10xfaster drafts
+22%organic traffic
1consistent brand voice
03Locked knowledge
Enterprise Knowledge

Critical knowledge buried in documents

Teams waste hours hunting through PDFs, wikis and drives for answers that already exist somewhere in the company.

💡Our fix: A RAG-powered knowledge assistant that answers questions from your own documents — accurately, with citations back to the source.
<5sto find answers
100%source-cited
-40%time on lookups
04Manual workflows
Operations

Repetitive, multi-step manual workflows

Staff copy-paste between tools, summarize, tag and route work by hand — slow, error-prone and impossible to scale.

💡Our fix: AI agents that read, decide and act across your tools to complete multi-step tasks — with human approval where it matters.
-60%manual effort
24/7throughput
error rates
05Generic experience
Personalization

One-size-fits-all customer experience

Static content and generic recommendations fail to engage, hurting conversion and retention.

💡Our fix: Generative personalization that tailors messaging, product recommendations and journeys to each user in real time.
+27%conversion
+15%retention
1:1experiences
What we build

Our Generative AI Development Services

End-to-end services that take you from a validated use case to a deployed, dependable AI product.

We help you identify high-ROI use cases, assess feasibility and risk, and build a pragmatic roadmap — so you invest in AI that actually pays off instead of chasing hype.

  • Use-case discovery & prioritization
  • Feasibility & data-readiness audit
  • ROI modelling & build-vs-buy analysis
  • Architecture & delivery roadmap
Get a free use-case assessment →

Purpose-built language solutions on top of leading foundation models — with prompt engineering, orchestration and fine-tuning tailored to your domain and data.

  • Prompt & context engineering
  • Model orchestration & routing
  • Domain fine-tuning (LoRA / QLoRA)
  • Evaluation & guardrails
Discuss your LLM project →

Context-aware conversational assistants for support, sales and internal operations — that understand intent, remember context and take action on your systems.

  • Support & sales copilots
  • Multi-channel (web, WhatsApp, Slack)
  • CRM / order-system integration
  • Human-handoff with full context
Build a chatbot →

Retrieval-augmented generation grounded in your own documents, so answers are accurate, current and cite their source — no hallucinations, no guesswork.

  • Document ingestion & chunking
  • Embeddings & vector search
  • Source-cited, grounded answers
  • Access control & permissions
Explore RAG solutions →

Data preparation, fine-tuning and rigorous evaluation to make models speak your brand's language, follow your rules and perform reliably on your tasks.

  • Dataset curation & labelling
  • Parameter-efficient fine-tuning
  • Evaluation harness & benchmarking
  • Open-source & on-prem options
Fine-tune a model →

Add AI to the apps you already run — WooCommerce stores, CRMs, ERPs, portals and internal tools — through clean, secure APIs, without rebuilding what works.

  • Secure API & SDK development
  • WooCommerce / e-commerce add-ons
  • Streaming & async pipelines
  • Rate-limiting & cost controls
Integrate AI into my app →

Autonomous and semi-autonomous agents that connect your tools and complete multi-step tasks — with human oversight and approvals where it counts.

  • Tool-using, multi-step agents
  • Workflow & process automation
  • Human-in-the-loop controls
  • Auditing & observability
Automate a workflow →

Generate and understand images, audio and video at scale — from marketing creative and product visuals to transcription, voice and video analysis.

  • Image & creative generation
  • Speech-to-text & voice AI
  • Video analysis & summarization
  • Brand-safe content pipelines
Explore multimodal AI →
Proven track record

A partner with the numbers to back it up

More than a decade shipping software — and applied AI that reaches production.

15+Years of experience
250+Projects delivered
100+Skilled Employees
350+Global clients
91%Client retention
4.9★Average client rating
250+Qualified Technologies
24/7Support & monitoring
Success stories

Real results from real deployments

A few examples of the outcomes generative AI can deliver when it is built right.

E-commerce

AI product-content engine

Challenge: A retailer's team couldn't write descriptions fast enough for a growing catalog.

Solution: A brand-tuned generation pipeline for descriptions, SEO meta and alt text with human review.

60%faster catalog
+22%organic traffic
Healthcare

Clinical document assistant

Challenge: Staff spent hours searching guidelines and drafting documentation.

Solution: A RAG assistant over approved clinical documents with strict access controls and citations.

-40%admin time
100%source-cited
Fintech

Support copilot

Challenge: Rising ticket volume was outpacing the support team's capacity.

Solution: An AI copilot that drafts responses and auto-resolves routine queries with human handoff.

55%auto-resolved
+18%CSAT

Not sure where AI fits in your business?

Get a free 30-minute use-case assessment from our AI team — no strings attached.

Get My Free Assessment →
Model-agnostic

Generative AI Models We Work With

We pick the right model for your accuracy, cost, latency and privacy needs — proprietary or open-source.

GPT-4o

OpenAI

Strong reasoning and multimodal support for broad, general-purpose applications.

Claude

Anthropic

Long-context understanding and safety — ideal for document-heavy, enterprise work.

Gemini

Google

Natively multimodal with tight Google Cloud and Workspace integration.

Llama

Meta

Open-source and self-hostable — great when data must stay on your infrastructure.

Mistral / Mixtral

Mistral AI

Efficient open models offering a strong balance of speed, cost and quality.

Stable Diffusion

Stability AI

High-quality, customizable image generation for on-brand creative at scale.

DALL·E

OpenAI

Reliable text-to-image generation for fast, flexible visual content.

Whisper

OpenAI

Accurate speech-to-text across many languages for voice and transcription.

How we deliver

Our Generative AI Development Approach

A transparent, milestone-based path from first idea to a monitored production system.

1

Discover

Define the use case, success metrics and constraints with your stakeholders.

2

Assess Data

Audit data readiness and run a quick spike to prove the approach before you commit.

3

Architect

Select models, design the pipeline and plan for security, cost and scale.

4

Build

Engineer prompts, retrieval, fine-tuning, APIs and the user experience.

5

Evaluate

Test accuracy, safety and bias with automated evals plus human review.

6

Deploy

Ship to your cloud, integrate with your stack and go live confidently.

7

Monitor

Track quality and cost in production with dashboards and alerting.

8

Optimize

Use real feedback to improve accuracy, latency and cost over time.

Let's scope your generative AI solution

Book a free, no-obligation consultation. We'll assess your use case, recommend an approach and give you a clear, transparent estimate.

★★★★★ Rated 4.9/5 across Clutch, Google & GoodFirms by 200+ clients
Deep expertise

Technical Expertise of Our AI Developers

Specialists across the full generative AI stack — not generalists learning on your budget.

✍️

Prompt & Context Engineering

Designing reliable prompts, context windows and structured outputs that behave consistently in production.

📚

RAG Architecture

Chunking, embeddings, retrieval strategies and re-ranking for accurate, grounded, source-cited answers.

🎛️

Fine-Tuning & Training

LoRA / QLoRA, instruction tuning and dataset curation to adapt models to your domain and tone.

🧮

Vector Search & Embeddings

Selecting embedding models and vector stores, and tuning them for relevance, speed and scale.

🔁

MLOps & LLMOps

CI/CD for models, versioning, prompt management, evaluation pipelines and observability.

🖼️

Multimodal AI

Combining text, image, audio and video models into cohesive, real-world applications.

🛡️

AI Guardrails & Evaluation

Safety filters, hallucination checks, red-teaming and automated quality scoring.

🗄️

Data Engineering

Pipelines to collect, clean and structure the data that powers reliable AI.

☁️

Cloud AI Deployment

Scalable, cost-aware deployments on AWS, GCP and Azure — cloud or on-prem.

Our toolkit

Technologies We Deploy for Generative AI

A modern, best-of-breed stack chosen for reliability, performance and cost efficiency.

Foundation Models & APIs

OpenAI Anthropic Claude Google Vertex AI AWS Bedrock Azure OpenAI Cohere

Frameworks & Orchestration

LangChain LlamaIndex Haystack Semantic Kernel Streamlit

Vector Databases

Pinecone Weaviate Milvus pgvector Chroma Qdrant

ML, Fine-Tuning & Data

PyTorch TensorFlow Hugging Face NumPy / Pandas DeepSpeed

Cloud, MLOps & Backend

AWS Google Cloud Azure Docker Kubernetes MLflow FastAPI Redis
Where we work

Industries We Serve

Domain-aware generative AI built around your workflows and compliance needs.

Client voices

What Our Clients Say

The reason 95% of our clients come back for their next project.

Video Testimonials

Why ZTS India

Why Businesses Choose ZTS India

A dependable engineering partner that ships — not just a demo shop.

🛡️

Security & privacy first

Strict access controls, private deployments and clear data-retention policies from day one.

🚀

Faster time-to-market

Battle-tested accelerators and reusable components get you to a working product in weeks.

🧩

Full-stack AI team

From model selection to frontend and DevOps, one team owns the entire solution.

💡

Business-first thinking

We optimize for ROI and adoption, not clever demos that never make it to production.

🤝

Flexible engagement

Fixed scope, dedicated teams or staff augmentation — pick what fits your budget.

🔧

Clean handover & support

Documented, source-controlled code with ongoing support and optimization options.

Ready to build with generative AI?

Tell us about your use case. We'll come back with a practical approach, a timeline and a transparent estimate — free.

No obligation · Response within 1 business day · NDA on request
Good to know

Frequently Asked Questions

It is the process of building applications powered by models that generate content — text, images, code, audio and more. In practice it means choosing the right model, grounding it in your data, adding guardrails and integrating it into a usable, reliable product.

A working prototype typically takes 3–6 weeks. A production-ready solution usually lands in 2–4 months depending on scope, data readiness and integrations. We start small and expand once value is proven.

Yes. We design for privacy from day one — private deployments, strict access controls and clear data-retention policies. Where required, we use models and cloud regions that keep your data within your compliance boundaries.

We are model-agnostic. We work with OpenAI, Anthropic Claude, Google Gemini and open-source options like Llama and Mistral, recommending the best fit for your accuracy, cost, latency and privacy needs.

Absolutely. We regularly add generative AI to existing platforms — WooCommerce and other e-commerce stores, CRMs, ERPs, portals and internal tools — through clean APIs, without rebuilding what already works.

We ground models in your data using RAG, add validation and guardrails, and run automated evaluations plus human review. For critical answers we require source citations so responses are verifiable.

Fixed-scope projects for well-defined work, dedicated teams for evolving products and staff augmentation to fill a specific skills gap. You can scale up or down as your roadmap changes.

Cost depends on scope, model usage and integrations. We offer fixed pricing for defined projects and flexible monthly rates for dedicated teams. Book a free consultation for a transparent estimate.

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