SolGuruz builds and ships production machine learning: custom models trained on your data, deployed behind reliable APIs, and monitored so accuracy holds as the data shifts. We own the work from problem framing through deployment and retraining.
From predictive analytics and computer vision to NLP, recommendation systems, and the MLOps that keeps them running, we focus on models that earn their place in production and keep delivering as your operations grow.
Flexible Engagement Models
Strict NDA
1 Week Risk-Free Trial
We build AI into real products, with a team that runs AI tooling across every stage of delivery.
Trusted by Startups and Enterprises Worldwide
Custom Software Development Success Stories
Real founders, CEOs, CTOs, and product owners behind 102+ shipped products across 14 industries share what working with SolGuruz looked like. Every story is one of 130+ independently verified client reviews across Clutch, Google, Glassdoor, and other platforms, averaging 4.9 ★★★★★ ratings.
Online Art Education Platform
I've been working with SolGuruz for almost five or six years. They say you have to pick two of the three: cost, quality, or speed. SolGuruz has been the only company that I have ever experienced that has delivered on all three of those pillars at the same time. They deliver the highest quality code, designs, and projects at the best price and within timelines you think are impossible. You guys are amazing and unmatched.
Vice President & Co-Founder, Sparketh | Shark Tank Featured Startup
Custom Software Solution Development / Driver Dashboard & Invoice Automation for Food Service Company
SolGuruz has delivered a solution that has reduced 90% of manual efforts through automation and provided real-time insights for supplier fulfillment and order volume trends. The team is responsive to requests and changes, and their proactive approach to problem-solving has stood out.
Summarized from Gary Boyd's Clutch review
Gary Boyd
CEO and Owner, Tasty Food Guys | Florida, USA
Mobile App & Web App Dev & UX/UI Design for Social Platform / Daily Journaling App
SolGuruz has delivered the initial design and meets weekly to track progress. The team coordinates the project through a project manager as the primary client contact. SolGuruz is communicative and provides follow-up to meet requirements. They communicate via virtual meetings, emails, and messages.
Summarized from Robert Mond's Clutch review
Robert Mond
Principal, The Master Storytellers LLC & Founder/CEO, DreamStoryLive | New Mexico, USA
Radon Compliance Software - Website & Mobile App Dev for Home Services Company
SolGuruz delivered the project on time and had outstanding project management skills. Furthermore, the team communicated effectively and cohesively through Microsoft Teams. Overall, the service provider's performance led to the client's satisfaction.
Summarized from Chad Smith's Clutch review
Chad Smith
Owner, Monarch Radon Testing LLC & Founder, RadonSketch | Colorado, USA
Rated 5.0 / 5 on Google by clients, partners, and visitors who have experienced SolGuruz first-hand - through our work, our office, or our team.
Read Google reviews →
4.9 / 5 on Clutch - independently audited reviews from real clients who have shipped products with SolGuruz.
Read Clutch Reviews →Backed by independent accreditations
Machine learning development services cover the design, training, deployment, and ongoing operation of ML models that learn patterns from data to make predictions or decisions. A vendor runs the full lifecycle: data preparation, feature engineering, model training and evaluation, production deployment, and monitoring for accuracy and drift.
Machine learning development, also called AI/ML development, is not the same as a one-off proof of concept. A model that scores well in a notebook is not a product. It has to serve predictions reliably under real traffic, retrain as the data shifts, and hold its accuracy over time. We build custom ML software that ships to production, with evaluation metrics, drift monitoring, and retraining wired in from the start.
our expertise
Custom machine learning across the capabilities that move business metrics, each built on your data, evaluated against real targets, and shipped to production.
We build regression and time-series models (gradient boosting, ARIMA, LSTM) on your historical data to forecast demand, churn, and revenue. Accuracy is tracked with RMSE and MAE so the numbers stay dependable once they hit production.
Image and video models for object detection, classification, OCR, and segmentation, trained on your labeled data and deployed for real-time or batch inference. We hold them to your accuracy targets using mAP and precision/recall, not a demo dataset.
Text models for classification, entity extraction, sentiment, and semantic search, built on transformer architectures and fine-tuned on your domain data. They handle your terminology and edge cases instead of a generic benchmark.
Collaborative filtering, content-based, and hybrid recommenders that rank products, content, or next-best actions per user. We validate offline with recall@k and NDCG, then A/B test online to prove lift before a full rollout.
Neural networks (CNNs, RNNs, transformers) for problems where classical models plateau, built with PyTorch or TensorFlow. We optimize for inference cost and latency at production scale, not just leaderboard accuracy.
CI/CD for models: automated training pipelines, a model registry with versioning, drift and data-quality monitoring, and scheduled retraining. This is how a shipped model keeps performing instead of silently degrading over weeks.
Feature pipelines, feature stores, and labeling workflows that turn raw and streaming data into clean, versioned training sets. Most ML failures trace back to the data, so we treat this as core work, not setup.
Machine learning consulting that scopes which problems are worth solving with ML, tests feasibility on your real data, and defines success metrics and evaluation up front. The point is to fund models that ship, not experiments that stall in a notebook.
Custom ML software built end to end for your problem, from framing and training through evaluation to deployment, for cases where off-the-shelf APIs cannot fit your data or accuracy needs. This is machine learning development.
Machine learning development, covers several model families. We pick the type that fits your data and the outcome you need, then build custom ML software around it, not a one-size-fits-all notebook.
Model families we train, evaluate, and ship to production
Models learn from labeled examples to predict an outcome, so a churn model trained on past customer records scores which accounts are likely to cancel next month.
Models find structure in unlabeled data, so a clustering model groups your users into behavior segments no one defined in advance for targeting and pricing.
An agent learns by trial and reward against a goal, so a pricing or logistics policy improves each decision from the results it sees, useful for dynamic pricing and route optimization.
Neural networks learn features directly from raw signals like images, audio, and text, so a computer vision model reads defects off a production line or extracts fields from scanned documents.
Models train on a small labeled set plus a large unlabeled one, so you get a working fraud or document classifier when hand-labeling every record is too slow or expensive.
We adapt a large pretrained model to your domain with a fraction of the data, so a foundation vision or language model is fine-tuned on your catalog or support tickets instead of trained from scratch.
Your Machine Learning Partner for Scalable Growth. We help you harness AI for automation, smarter decisions, and long-term sustainability.
Machine learning pays off when it is applied to the right stage with the right data. Here is where it helps most across your product and operations.
Predict market demand, analyze user behavior, competitive analysis
AI-based data filtering, fraud detection, and recommendations
AI chatbots, voice interfaces, image recognition, and personalization
Predict churn, optimize features, segment users, automate support
We don't believe in delays or surprises. Our machine learning development workflow is a lean, powerful engine, built to launch your product fast with flawless architecture, total transparency, and unwavering focus on your goals.
Every successful machine learning journey begins by deeply understanding your business and the problem you're trying to solve.
Outcome: A well-defined use case where AI or ML can bring real value, backed by business logic - not just hype.
- Dive into your current workflows, pain points, and goals..
- Learn about your future goals and the challenges you are currently facing.
- Take a deep look at your current workflows and tools to identify where we can fit in machine learning to create an impact. For instance, automating repetitive tasks, etc.
- Assess the feasibility of machine learning based on available data and infrastructure..
Machine learning is only as strong as the data that powers it.
Outcome: A clean, structured, and usable dataset ready to train high-quality models.
- Identify data sources (internal + external).
- Plan pipelines for cleaning, labeling, transformation, and ingestion.
- Define data governance and quality checks to ensure long-term success.
Once we’ve framed the problem and prepped the data, we architect intelligent systems that actually solve it.
Outcome: A working machine learning prototype (PoC or MVP) tailored to your specific use case.
- Choose the right algorithms (e.g., regression, classification, deep learning).
- Build and test small-scale models quickly to validate approach.
- Iterate fast with business feedback loops.
This is where your system starts getting smart.
Outcome: A fully trained model that performs reliably in real-world conditions.
- Train models using structured pipelines on GPU/TPU environments.
- Use metrics like precision, recall, F1, RMSE to evaluate model performance.
- Optimize for bias, overfitting, and scalability.
Machine learning shouldn’t live in silos, it should power your software, systems, and decisions.
Outcome: A production-ready machine learning model integrated into your existing or new app, backend, or cloud environment.
- Build APIs or microservices to expose model predictions.
- Deploy to cloud (AWS / GCP / Azure) or edge devices based on your needs.
- Secure, containerize, and document everything for easy ops handoff.
Your AI doesn’t stop learning after launch. Neither do we.
Outcome: An machine learning system that evolves with your users, your data, and your business goals.
- Set up real-time model monitoring dashboards.
- Create pipelines for retraining with fresh data.
- Support A/B testing, user feedback loops, and continuous improvement.
MLOps is the engineering discipline that moves a machine learning model from raw training data to a monitored production service and keeps it accurate as data changes over time. It matters because a model that scores well in a notebook still fails in production without pipelines, versioning, and drift detection.
We build repeatable pipelines that clean, label, and transform raw data into versioned feature sets, so every training run uses the exact inputs your production model will see at inference time.
We train and tune models against your business objective while tracking every experiment (hyperparameters, dataset version, and code commit), so a strong result can be reproduced later, not just remembered.
We measure each model on the metrics that fit the problem (F1, precision, and recall for classification, AUC for ranking, RMSE for regression) plus slice-level checks so accuracy holds across customer segments, not just on average.
We package the model behind a versioned API or scheduled batch job and run the same preprocessing code in serving as in training, which prevents the train/serve skew that quietly degrades live predictions.
We monitor live predictions for data drift, concept drift, and latency, and alert your team when input distributions or accuracy move outside the thresholds we agree on up front.
We version both models and datasets and retrain on a schedule or a drift trigger, promoting a new model to production only after it beats the current one on held-out data.
You’ve seen the framework. Now let’s apply it to your real-world challenges, from automation to predictive insights.
102+Products Shipped Across Industries
14Industries Served
99.9%On-Time Delivery Rate
90+Team Members
Hire from our talented pool of developers with years of experience in your industry. Look at our flexible hiring models: Flexible hiring models make hiring developers easier and more efficient for businesses of all sizes, allowing access to top talent and cost-effective solutions.
Want someone focused completely on your project? Hire a Dedicated Machine Learning Developer who work full-time or part-time, just like they're part of your own team.
You get -
You can also easily change how many developers you need as your project changes, making sure you always have the right amount of help.
Hire Dedicated Developers by the hour. Need an extra hand for specific tasks, fixing glitches, or just some quick support? Get the help you need without any long-term commitments.
You get -
Boost Your Team - Need extra hands on deck?
Quickly hire remote MERN Stack developers to join your current team. They act as an extension of your in-house team. Speed up the process to get things done on time.
You get -
Apply domain-specific machine learning expertise to accelerate deployment and reduce implementation risk. Our machine learning developers bring hands-on experience across industries such as:
Healthcare
Fitness & Wellness
Real Estate
Travel & Hospitality
Food Delivery
Fintech
Education
Media & Entertainment
E-commerce & Retail
Supply Chain & Logistics
Automotive & Mobility
Sports
As your AI/ML development company, we don’t just pick trendy tools; we choose the tech stack that fits your business goals, data needs, and future growth.
Here's a quick look at what we often use when building custom machine learning solutions:
TensorFlow
PyTorch
OpenCV
Hugging Face
Kaggle
OpenAI
Gemini
Anthropic
Ollama
Claude
Voiceflow
Vapi AI
Perplexity.Ai
Stable Diffusion
CrewAI
N8n
Langflow
Keras
LangChain
Google Colab
Rasa
Llama 4
PaLM 2
TensorFlow
PyTorch
OpenCV
Hugging Face
Kaggle
OpenAI
Gemini
Anthropic
Ollama
Claude
Voiceflow
Vapi AI
Perplexity.Ai
Stable Diffusion
CrewAI
N8n
Langflow
Keras
LangChain
Google Colab
Rasa
Llama 4
PaLM 2
We train models on client data under ISO 27001:2022 and ISO 9001:2015, SOC 2-aligned hardening, and a signed BAA when an engagement touches production PHI. Training data, feature stores, model artifacts, and inference endpoints are access-controlled, encrypted in transit and at rest, and handled so your data is never used to train models for anyone else.
SolGuruz holds ISO 27001:2022 (information security) and ISO 9001:2015 (quality management) certifications. Your ML datasets, model weights, and pipeline configs sit inside that documented ISMS: role-based access, audit logging, and change control across the training and deployment lifecycle.
We build to SOC 2-aligned controls, we are not SOC 2 certified. That means least-privilege access to training data and MLOps infrastructure, encryption of data at rest and in transit, secrets management, and audit trails on who accessed which dataset, ran which training job, and promoted which model to production.
We sign a Business Associate Agreement when a project accesses production PHI; we hold no HIPAA certification. Model development, QA, and evaluation run on synthetic or de-identified data by default, so real patient records only enter the pipeline when the contract and controls require it.
Data handling is designed in from the first pipeline, not bolted on later. Training data is isolated per client, PII is minimized or masked before it reaches feature engineering, and model artifacts, embeddings, and inference logs are scoped so data from one client can never leak into the features or predictions of another.
Independent security agencies run penetration tests and audits against the systems that serve your models; we build to comply and remediate their findings. We do not self-certify our own pen-testing. Model APIs and data pipelines are tested for the same access, injection, and exfiltration risks as any production service.
Our approach to machine learning development delivers results where others fall short.
Create and customize your smart projects with the best custom machine learning development company in India.
Work with the best and see the difference!
End-to-End Development Expertise
Consider us your end-to-end AI partner - we manage everything from initial data collection to putting your AI development lifecycle into action.
Industry-Specific Solutions
We develop AI applications with a deep understanding of your vertical’s unique challenges and opportunities.
Future-Proof Technology
Our AI solutions evolve with your business, continually learning and improving their performance.
We help you harness AI for automation, smarter decisions, and long-term sustainability - without overcomplicating your operations.
From Our Portfolio
SolGuruz has shipped 102+ products across 14 industries. See how SolGuruz built production AI and machine learning systems - fitness intelligence, healthcare scheduling, language tools, and workflow automation - that deliver measurable value in real-world deployments.
AI-Powered Fitness App Solution
Explore how SolGuruz created an AI-powered fitness app that enhances personal training with features like meditation, workouts, exercises, fitness challenges, and a meal and diet planner.
Key Outcomes
AI-Powered Healthcare Staffing App Solution
Explore our AI-powered healthcare staffing app case study. See how SolGuruz’s expertise transforms nurse staffing challenges into seamless solutions.
Key Outcomes
AI Clinical Notes Platform That Turns 2-Hour Documentation Into One Click
NoteCliniq transforms clinical conversations into HIPAA-compliant SOAP notes in seconds, eliminating 2+ hours of manual documentation daily for busy clinicians.
Key Outcomes
AI-Powered Trip Planner App Solution
Explore how SolGuruz created an AI-powered trip planner app. It is an exclusive AI vacation planner that helps with finding hotels, cabs, places, and complete itineraries.
Key Outcomes
Explore the latest reviews from our existing clients to get a better picture of our services and collaboration.
EdTech Platform Development
SolGuruz has delivered the project on time, meeting the client's expectations. They have communicated frequently and promptly via virtual meetings, ensuring an effective workflow. Their responsiveness has been a hallmark of their work.
From the verified Clutch review by
CTO, Education Company
Germany
UI/UX Design & Research for Mobile App for Tech Startup
SolGuruz's efforts have led to extensive research into apps, and their work has met the client's expectations. The team meets deadlines, stays within budget, and has demonstrated remarkable communication skills throughout the engagement. SolGuruz's attention to detail is a hallmark of their work.
From the verified Clutch review by
CEO/Freelancer, Tech Startup
United Kingdom
UX/UI Design, Prototyping & Graphic Design for AI Company
SolGuruz has finished the designs for the various items requested, and the client has received positive stakeholder feedback. SolGuruz's project management is good, and they deliver on time. The client also praises the team's accommodation of changing requirements.
From the verified Clutch review by
Founder & CEO, AI Company
Fremont, California, United States
Machine learning is one part of the AI work we do. When your project needs a different capability, these teams pick up where ML leaves off.
The full range of AI development and enablement services, with machine learning as one capability among agents, LLMs, and generative AI.
Content generation, image and multimodal output, RAG copilots, and knowledge assistants built on generative AI models.
Autonomous and assistive agents that use tools, follow multi-step workflows, and take action inside your systems.
Connect trained models and AI APIs into your existing apps, data, and workflows without a full rebuild.
Strategy, feasibility, and a prioritized roadmap that maps AI use cases to real business outcomes.
Ship a first version fast to validate an ML-powered product idea before committing to the full build.
Quick answers to the questions our clients and prospects ask most. If yours is not here, our team is one click away.
Need advice tailored to your project?
FAQs cover the common ground. For decisions specific to your tech stack, timeline, and team, talk directly to a senior engineer who has shipped what you are planning.
