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Learn how we have transformed healthcare operations through intelligent AI-powered automation.
Discover how Narwal transformed a global industry leader’s data platform, harmonizing data across systems to enable advanced analytics, improve decision-making, and ensure scalability for 1M+ merchants worldwide.
At Narwal, we blend foundational data science with advanced machine learning to unlock actionable intelligence from data. Our team applies techniques such as deep learning, NLP, computer vision, and reinforcement learning to build models that are not only accurate but scalable and production-ready.
Leveraging AutoML, ensemble modeling, transfer learning, and drift detection, we tailor solutions that drive measurable outcomes ensuring transparency through Explainable AI (XAI) and performance optimization at every stage of the ML lifecycle.
Deploy LLMs, retrieval-augmented generation, and agentic workflows to transform how decisions, content, and operations are executed across any industry.
Models trained on labeled data
Discovering patterns without labels
Understanding text and images
Neural nets & reward-based training
XAI, Transparent model decision reasoning
Tailor models with ensemble learning, AutoML practices, transfer learning, and hallucination detection to build robust, production-ready AI systems.
Combining multiple models’ predictions.
Automating ML pipeline creation
Reusing knowledge across tasks
Identifying data distribution shifts
AI evaluating output and enforcing rules
Detecting model’s false outputs
Harness the potential of next-gen generative models to create human-like content, automate workflows, and power dynamic experiences. From large language models and multi-modal learning to prompt engineering and agentic orchestration,
our capabilities enable businesses to deliver intelligent solutions that are creative, adaptive, and efficient, accelerating innovation across enterprise functions.
Deploy LLMs, retrieval-augmented generation, and agentic workflows to transform how decisions, content, and operations are executed across any industry.
Large AI models for text generation, analyzing images and multimodal reasoning tasks.
Generative AI enhanced by retrieved data.
Designing prompts to guide AI output.
Linked AI tasks and autonomous agents.
Graph structures powering generative AI.
Design conversational bots, graphs, and agentic workflows using fine-tuned LLMs. Ensure safe deployment through guardrails like toxicity detection and prompt injection control.
AI agents conversing and assisting users.
Combining multiple models’ predictions.
Data stores and graphs powering access bots.
Automated bots orchestrating business workflows.
AI generating code, tests, and synthetic data.
Customizing LLMs on specific datasets.
AI evaluating output and enforcing rules.
We develop intelligent autonomous agents that mimic human decision-making, handle multi-step tasks, and adapt to evolving contexts. Leveraging agentic RAG, multi-agent systems, and human-in-the-loop orchestration, our AI agents unlock
new levels of efficiency and personalization whether for document processing, virtual assistance, or dynamic customer interactions.
Create autonomous agents that think, learn, and act—executing multi-step logic, automating decisions, and adapting in real time.
Autonomous retrieval-augmented generation
AI systems engaging in conversations
AI bots automating workflows
Collaborative networks of AI agents
Agents handling text, images & audio
Agents handling text, images & audio
Build intelligent agents and custom AutoGPTs that learn, adapt, and collaborate with humans enabling real-time orchestration and task automation.
AI extracting structured data from docs
Coordinating tasks among AI agents
AI refined through human feedback loops
Platforms for coordinating multiple AI agents
Tailored autonomous GPT‑based agents
Our MLOps solutions ensure that AI models are not only built, but efficiently deployed, monitored, and optimized at scale. By automating pipelines and integrating tools like Kubeflow, MLFlow, and Langfuse, we enable faster iterations, robust version control, and proactive monitoring empowering businesses to maintain high-performing ML systems in real-time production environments.
Automate the full ML lifecycle pipeline creation, drift monitoring, and real-time observability to keep models performing at scale.
Automated orchestration of ML workflows
Periodic model monitoring, retraining & tuning
Managing LLM deployment & operations
Agent Monitoring: Tracking autonomous agent performance
Billing: Optimizing ML infrastructure costs
Unified logs, metrics & traces
Engineer end-to-end pipelines, track model performance, and monitor drift using tools like Langfuse and MLFlow all with built-in observability and compliance.
Combining AI automation with human oversight
Custom ML workflow architecture
AI extracting structured data from docs
Coordinated versioned multi‑step ML workflows
Assessing ML model performance & quality
Centralized model storage & versioning
Narwal’s advisory services bridge the gap between vision and execution. We guide enterprises in building ethical, scalable, and compliant AI strategies tailored to business goals and industry standards. With a business-first mindset, we help define roadmaps, identify impactful use cases, and enable sustainable AI adoption for long-term growth and transformation.
Automate the full ML lifecycle pipeline creation, drift monitoring, and real-time observability to keep models performing at scale.
Assessing organization’s AI readiness
Planning AI objectives and roadmap
Selecting and ranking AI use cases
Selecting AI tools and platforms
Ensuring ethical AI and legal compliance
Tracking and tuning AI performance
Assess AI readiness, define strategic roadmaps, and guide ethical, scalable implementations tailored to business objectives and industry regulations.
Aligning AI with business goals
Leveraging industry‑specific knowledge
Guidelines for responsible AI use
Managing organization‑wide AI adoption
Evaluating impact of AI initiatives
At Narwal, we blend foundational data science with advanced machine learning to unlock actionable intelligence from data. Our team applies techniques such as deep learning, NLP, computer vision, and reinforcement learning to build models that are not only accurate but scalable and production-ready.
Leveraging AutoML, ensemble modeling, transfer learning, and drift detection, we tailor solutions that drive measurable outcomes ensuring transparency through Explainable AI (XAI) and performance optimization at every stage of the ML lifecycle.
Deploy LLMs, retrieval-augmented generation, and agentic workflows to transform how decisions, content, and operations are executed across any industry.
Models trained on labeled data
Discovering patterns without labels
Understanding text and images
Neural nets & reward-based training
XAI, Transparent model decision reasoning
Tailor models with ensemble learning, AutoML practices, transfer learning, and hallucination detection to build robust, production-ready AI systems.
Combining multiple models’ predictions.
Automating ML pipeline creation
Reusing knowledge across tasks
Identifying data distribution shifts
AI evaluating output and enforcing rules
Detecting model’s false outputs
Harness the potential of next-gen generative models to create human-like content, automate workflows, and power dynamic experiences. From large language models and multi-modal learning to prompt engineering and agentic orchestration,
our capabilities enable businesses to deliver intelligent solutions that are creative, adaptive, and efficient, accelerating innovation across enterprise functions.
Deploy LLMs, retrieval-augmented generation, and agentic workflows to transform how decisions, content, and operations are executed across any industry.
Large AI models for text generation, analyzing images and multimodal reasoning tasks.
Generative AI enhanced by retrieved data.
Designing prompts to guide AI output.
Linked AI tasks and autonomous agents.
Graph structures powering generative AI.
Design conversational bots, graphs, and agentic workflows using fine-tuned LLMs. Ensure safe deployment through guardrails like toxicity detection and prompt injection control.
AI agents conversing and assisting users.
Combining multiple models’ predictions.
Data stores and graphs powering access bots.
Automated bots orchestrating business workflows.
AI generating code, tests, and synthetic data.
Customizing LLMs on specific datasets.
AI evaluating output and enforcing rules.
We develop intelligent autonomous agents that mimic human decision-making, handle multi-step tasks, and adapt to evolving contexts. Leveraging agentic RAG, multi-agent systems, and human-in-the-loop orchestration, our AI agents unlock
new levels of efficiency and personalization whether for document processing, virtual assistance, or dynamic customer interactions.
Create autonomous agents that think, learn, and act—executing multi-step logic, automating decisions, and adapting in real time.
Autonomous retrieval-augmented generation
AI systems engaging in conversations
AI bots automating workflows
Collaborative networks of AI agents
Agents handling text, images & audio
Agents handling text, images & audio
Build intelligent agents and custom AutoGPTs that learn, adapt, and collaborate with humans enabling real-time orchestration and task automation.
AI extracting structured data from docs
Coordinating tasks among AI agents
AI refined through human feedback loops
Platforms for coordinating multiple AI agents
Tailored autonomous GPT‑based agents
Our MLOps solutions ensure that AI models are not only built, but efficiently deployed, monitored, and optimized at scale. By automating pipelines and integrating tools like Kubeflow, MLFlow, and Langfuse, we enable faster iterations, robust version control, and proactive monitoring empowering businesses to maintain high-performing ML systems in real-time production environments.
Automate the full ML lifecycle pipeline creation, drift monitoring, and real-time observability to keep models performing at scale.
Automated orchestration of ML workflows
Periodic model monitoring, retraining & tuning
Managing LLM deployment & operations
Agent Monitoring: Tracking autonomous agent performance
Billing: Optimizing ML infrastructure costs
Unified logs, metrics & traces
Engineer end-to-end pipelines, track model performance, and monitor drift using tools like Langfuse and MLFlow all with built-in observability and compliance.
Combining AI automation with human oversight
Custom ML workflow architecture
AI extracting structured data from docs
Coordinated versioned multi‑step ML workflows
Assessing ML model performance & quality
Centralized model storage & versioning
Narwal’s advisory services bridge the gap between vision and execution. We guide enterprises in building ethical, scalable, and compliant AI strategies tailored to business goals and industry standards. With a business-first mindset, we help define roadmaps, identify impactful use cases, and enable sustainable AI adoption for long-term growth and transformation.
Automate the full ML lifecycle pipeline creation, drift monitoring, and real-time observability to keep models performing at scale.
Assessing organization’s AI readiness
Planning AI objectives and roadmap
Selecting and ranking AI use cases
Selecting AI tools and platforms
Ensuring ethical AI and legal compliance
Tracking and tuning AI performance
Assess AI readiness, define strategic roadmaps, and guide ethical, scalable implementations tailored to business objectives and industry regulations.
Aligning AI with business goals
Leveraging industry‑specific knowledge
Guidelines for responsible AI use
Managing organization‑wide AI adoption
Evaluating impact of AI initiatives
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