Our AI/ML experts improved response accuracy by training a GPT model according to specific client requirements.
Hire Generative AI Developers
Build systems capable of synthesis, reasoning, and high-fidelity content generation.
Unlike traditional, rule-based AI that only classifies data, generative intelligence interprets intent to produce structured, domain-specific outputs. Our generative AI experts specialize in building this intelligence by fine-tuning LLMs and grounding these models with RAG (Retrieval-Augmented Generation).
- Convert repositories of PDF manuals, emails, and call transcripts into AI training datasets
- Move from rigid "if-then" logic to build AI models that can interpret complex instructions, resolve ambiguities, and generate human-readable explanations
- Refine models using Supervised Fine-Tuning (SFT) and RLHF (Reinforcement Learning from Human Feedback) to ensure the AI speaks your industry’s language
- Right-size your gen AI workflows, using smaller, high-performance models to handle routine generation tasks
Managed Talent. Engineered for Accountability.
Dedicated Full-Time Engineers
FTEs only No freelancers or gig marketplace.
Experienced Talent
Vetted Experts Rapid Deployment
Managed Operations
Senior oversight Time & Task Monitoring
Workflow-Ready Integration
Jira Slack GitHub Teams
Global Overlap
All Time Zones 24/7 Support
Security
ISO 27001 & CMMI3 NDA & IP Secure
Send an Inquiry
Our Services
Comprehensive Generative AI Development Services
Build custom-trained models that perform complex reasoning and generate structured outputs within your business environment. Our Generative AI developers replace generic API-calling with fine-tuned LLMs and RAG architectures for maximum accuracy and reliability.
Generative AI Consulting
Get a practical Generative AI Roadmap centered on token economics and architectural feasibility. Our generative AI consultants conduct deep-dive audits to identify opportunities across content generation, knowledge assistance, document intelligence, and Agentic workflow automation. Based on this, we determine the ideal generative AI application (Copilots, Agents, Chatbots, or Decision Support Systems) while guiding Model Selection and Deployment Strategy.
Generative AI Model Engineering
Hire Generative AI developers to architect stateful, Reasoning-Based Generative Engines. Using transformer-based ML models, GANs, and Diffusion Architectures, we design memory-aware generative AI solutions that retain context across long-running interactions. All our solutions support humans-in-the-loop checkpoints, allowing your subject matter experts to evaluate AI outputs before they reach production. By bridging the gap between raw probabilistic models and enterprise logic, we deliver reliable generative AI systems that turn natural language prompts into actionable machine-readable instructions.
Generative AI Model Replication
Replicate the performance and generative DNA of proprietary LLMs. Hire generative AI engineers to capture the reasoning patterns and instruction-following capabilities of frontier models like GPT-4o or Claude 3.5 Sonnet. We replicate these capabilities into smaller, open-weight/ open-source models such as Llama 3.2 or Mistral 8x22B. By mirroring the Latent Space and output distribution of ‘teacher’ models, we ensure your local deployments generate text and logic matches industry leaders without external API dependencies.
Multimodal AI Development
Bridge the sensory gap by building models that can Cross-Generate between text, vision, and sound. Hire gen AI engineers to deploy systems where an image reference can be used to generate a video, or a text prompt can synthesize a high-fidelity audio briefing or a visual dashboard. We implement Cross-Modal Embedding and Diffusion techniques, allowing your enterprise to generate rich, multi-dimensional content that reacts to real-world visual and auditory inputs.
RAG Pipeline Development
Empower your generative AI models to "cite their sources," grounding outputs in your proprietary facts. Hire generative AI developers to build custom RAG pipelines that feed your proprietary high-signal data into the model’s Context Window, allowing it to generate deep-dive technical summaries and insights based purely on your internal records. By combining Semantic Retrieval with generative synthesis, we ensure the model doesn't just "find" information but actively re-interprets and summarizes it for specific stakeholders.
Model Integration and Deployment
Embed Generative Intelligence directly into your operational core via secure API integrations to automate cognitive tasks. Our gen AI developers implement Server-Sent Events to ensure your models are not just conversing but actively generating invoices, drafting emails, or synthesizing meeting minutes within your existing systems (SAP, Microsoft Dynamics 365, Salesforce, etc). We focus on Streaming Inference and asynchronous processing to ensure that as the model generates content token-by-token, it is reflected in your UI with sub-second latency for a fluid, assistive user experience.
Generative AI Model Fine-Tuning
Hire Generative AI engineers to embed your unique brand voice and domain-specific terminology directly into the model's neural weights. Our developers use PEFT (Parameter-Efficient Fine-Tuning) techniques, such as LoRA and QLoRA, to fine-tune large language models on your proprietary datasets. We shift the generative baseline to produce high-accuracy outputs, such as legal briefs following specific jurisdictional rules or medical reports using precise clinical terminology via Supervised Fine-Tuning (SFT).
Generative AI Performance Optimization
Hire Generative AI engineers to optimize latency, throughput, and inference cost across your LLM stack. We benchmark Time to First Token (TTFT), inter-token latency, and output speed to establish a baseline. Our gen AI experts then improve performance through Prompt Footprint Reduction, cache-aware request design, model routing, and back-end inference tuning. In self-hosted environments, we also apply techniques such as speculative decoding, KV-cache optimization, and quantization-aware deployment to improve responsiveness under real production workloads.
Support and Maintenance for Generative AI
Hire Generative AI engineers for ongoing support that ensures the long-term reliability and accuracy of your models through rigorous, proactive LLMOps. We handle complex technical migrations to newer frontier architectures while monitoring Model Drift and prompt injection vulnerabilities in real time. By implementing continuous A/B testing and automated regression checks, we prevent quality degradation as your datasets and global AI standards evolve.
Ready to Architect Your Enterprise Generative Intelligence?
Stop experimenting with standalone prompts and basic Gen AI tools that everyone has access to. Our Generative AI engineers are ready to help you build something unique and proprietary.
Consult Our Generative AI Experts
Generative AI Specializations
Choose from the exact engineering expertise you need to scale your generative AI workflows.
LLM Engineers
GenAI specialists with mastery in working with frontier models, configuring them into cost-effective, domain-expert LLMs.
Focus: Core architecture, model fine-tuning, and performance benchmarking.
RAG Developers
Experts in building "Zero-Hallucination" AI frameworks by grounding generative outputs in your proprietary real-time data silos.
Focus: Retrieval-Augmented Generation and vector database orchestration.
LangChain Developers
Generative AI specialists in utilizing LangGraph and LlamaIndex to build LLM-powered, context-aware app ecosystems.
Focus: Building stateful, multi-step chains and agentic reasoning loops.
Prompt Engineers
Generative AI engineers who work on prompts as production code, implementing CoT and ReAct patterns to slash token costs and ensure 100% output consistency.
Focus: Logic-layer architecture and token optimization.
OpenAI Developers
Gen AI experts who oversee ChatGPT models, the implementation of Assistant APIs, function calling, and multimodal (Vision/Audio) integration for immediate market readiness.
Focus: Rapid deployment and integration within the OpenAI ecosystem.
Llama Engineers
Experts who deploy Meta’s high-performance open-source models on private VPCs, ensuring complete control and total data privacy.
Focus: On-premise deployment, data sovereignty, and custom quantization.
Latest Blogs
Stay informed with the latest tech trends, AI updates, and expert opinions.
Tech Stack
- Orchestration LangGraph CrewAI LangChain Semantic Kernel LlamaIndex
- Model Layer GPT-4o Claude 3.5 Llama 3.2 Mistral 8x22B Gemini 1.5 Pro
- Vector Storage Pinecone Milvus Weaviate Qdrant pgvector (PostgreSQL)
- Integration FastAPI Pydantic Node.js gRPC Server-Sent Events (SSE)
- LLMOps LangSmith Langfuse Weights & Biases Arize Phoenix Giskard
- Infrastructure NVIDIA H100/A200 GPUs Docker Kubernetes (K8s) AWS Trainium
Frequently Asked Questions
Hire Generative AI Engineers: FAQs
No. When you hire a generative AI expert from our team, we prioritize data sovereignty. We use private VPC deployments and "Zero-Retention" API configurations to make sure your data stays within your infrastructure. Our ISO-certified generative AI development company also provides custom NDAs and NCAs with related clauses, ensuring maximum data privacy and security.
We build custom RAG (Retrieval-Augmented Generation) pipelines. Our generative AI developers implement "Guardrail" layers and "Grounding" techniques that force the model to retrieve facts from your verified documents before generating a response.
Standard software engineering is very logic-guided (if X, then Y), while AI is probabilistic. A generative AI engineer understands this, along with related concepts such as latent space, context window management, and resource scaling. They are also versed in the "stochastic" nature of LLMs, ensuring that the output remains consistent and machine-readable for your existing databases and ERP systems.
Yes. High costs usually stem from "model over-provisioning." Our gen AI consulting company can help you with model right-sizing, swapping expensive frontier models for smaller, fine-tuned versions (like Mistral or Phi-3) for routine tasks.
A basic PoC takes a few weeks, but a production-ready engine requires a few months. Contact our generative AI development company at info@suntecindia.com for a custom quote and timeline estimate.
Absolutely. You can hire remote generative AI developers from us; they integrate directly into your GitHub/GitLab workflows and Jira boards. All our developers are trained to join your existing sprint cycles without much knowledge transfer.