What can your Generative AI developers build?

They specialize in building AI chatbots, copilots, content generators, and data-driven AI tools using the latest LLM frameworks.

Which models and APIs do you use?

We work with OpenAI GPT-4, Claude, Mistral, LangChain, and Pinecone for vector-based retrieval and context-aware AI.

Can we integrate the AI with our existing systems?

Yes, we can integrate AI into CRMs, databases, and internal tools through secure APIs.

Do you support model fine-tuning?

Absolutely. We offer fine-tuning services for domain-specific data and proprietary use cases.

Hire Generative AI Developers

Generative AI is reshaping how businesses operate—from automated content creation and summarisation to intelligent agents that handle complex workflows. At CognyX AI, we connect you with elite generative AI developers who bring deep expertise in large language models, retrieval augmented generation (RAG), AI agents, prompt engineering, and multimodal solutions. Partner with us to accelerate innovation, reduce costs, and deliver superior experiences.

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Why hire generative AI developers from CognyX AI?

Vetted expertise

Our developers are hand-selected for their experience with state-of-the-art models like GPT-4o, Claude, Mistral, and Llama, as well as open-source frameworks such as LangChain, LangGraph, and vLLM.

End-to-end solutions

We handle everything from ideation and data strategy to model training, fine-tuning, and deployment — no multiple vendors required.

Secure and compliant engineering

All solutions are built with encryption at rest and in transit, role-based access control, audit trails, and region-aware hosting to meet compliance requirements.

Flexible engagement

Choose from fixed-scope proof-of-concepts, monthly retainers, or dedicated development pods, depending on your needs and budget.

Transparent pricing and timelines

We provide clear quotes and project plans before work begins, and we guarantee a dedicated point of contact throughout the engagement.

Local time zone overlap

Our global team ensures at least four hours of daily overlap with your business hours to streamline collaboration.

Our generative AI services

Large language model (LLM) development

Custom model fine-tuning — Tailor foundation models to your domain using supervised fine-tuning, parameter-efficient adapters (LoRA, QLoRA), and instruction tuning.

Retrieval Augmented Generation (RAG) — Build RAG pipelines that ground model outputs in your proprietary knowledge base, delivering accurate, citation-aware responses and improving trustworthiness.

Prompt engineering and safety — Design prompts and guardrails for zero-shot, few-shot, or chain-of-thought tasks. Implement content moderation, PII detection, and safe output filtering.

AI agents and automation

Task-oriented agents — Automate workflows like ticket triage, scheduling, data entry, and system integration using multi-tool agents orchestrated through frameworks such as LangGraph.

Human-in-the-loop interactions — Include approval steps within Slack, Teams, or other channels to ensure quality control and compliance.

Monitoring and analytics — Track agent performance, capture feedback, and iterate on prompts to continuously improve.

Voice and multimodal generative AI

Voice agents — Build natural conversation agents for phone or chat that can triage queries, place orders, or schedule appointments. Use high-quality voices with low latency and barge-in support.

Vision and image generation — Create models that understand and generate images or video, enabling product design, marketing content creation, and document recognition.

Predictive analytics and classical machine learning

Demand forecasting, pricing, and anomaly detection — Use time-series and classical ML models where generative methods are not necessary but still deliver business value.

Integration with analytics dashboards — Expose model outputs through user-friendly dashboards tailored for your team.

Industries and use cases

Healthcare

Automate patient intake, summarise clinical notes, and build triage agents that comply with health data standards.

Financial Services

Develop chatbots for KYC, generate personalised financial advice, and automate compliance workflows.

Manufacturing

Automate quality inspection using vision models, optimise inventory with predictive analytics, and deploy voice assistants on factory floors.

Education

Build tutoring bots and adaptive content generation tools that tailor learning to individual styles.

Retail & E-Commerce

Personalise recommendations, power dynamic search, and automate customer service chats.

Media & Marketing

Generate campaign copy, summarise research, and create multimedia assets at scale.

Our process for hiring your generative AI developer

Discovery

We host a free consultation to understand your objectives, available data, and success metrics.

Requirement & scoping

We prepare a project scope, propose engagement models, and outline budget options.

Matching & onboarding

We select developers with the right skill set and domain knowledge. Onboarding usually begins within 5–10 business days once paperwork and data access are finalised.

Build & iterate

Our team works in short sprints, delivering incremental features and incorporating feedback.

Launch & support

We deploy the solution, monitor usage, and provide continued support, bug fixes, and performance optimisation.

Case studies (examples)

Generative summarisation for a legal firm

We built a RAG-based copilot that ingests case law and contracts, reducing research time by 35% and improving accuracy through citation-aware responses.

Voice agent for a healthcare provider

Our team developed a voice assistant that schedules appointments and answers insurance queries. The agent handles 62% of calls without human intervention and integrates with the client’s CRM.

Marketing content generation for an ecommerce brand

Using a fine-tuned LLM, we automated product description creation, generating unique copy for 15,000 SKUs in a week and improving click-through rates by 18%.

Engagement models and pricing

Model	Description	Ideal for	Starting price (approx.)
Proof-of-concept sprint	A fixed-scope project lasting 2–4 weeks. Focus on a single workflow or feature to validate feasibility.	Startups or teams testing generative AI use cases	INR 2.5 – 4.5 lakh
Monthly retainer	Ongoing access to a generative AI engineer or small team. Includes continuous improvements and support.	Companies needing regular enhancements and maintenance	INR 6 – 15 lakh per month
Dedicated pod	A cross-functional team (architect, engineers, QA) dedicated full-time to your project. Includes weekly planning and monthly progress reviews.	Enterprises with complex projects or multiple use cases	INR 20 – 35 lakh per month

*All prices are approximate and may change. Receive a formal quote after the discovery phase.

FAQ

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