Who we help
As a machine learning consulting company with years of on-the-ground experience in crafting stable, high-performing, and scalable intelligent systems, we step in to guide and support organizations at any phase of ML maturity.
Expanding automation, enabling hyper-personalized user experience, boosting decision-making precision – whatever drives your AI/ML adoption, it should start with forward-thinking choices before you invest in full-scale development. Our practice-proven machine learning consulting services meet you where you are, spanning:
We parlay our 25+ years of tech knowledge into custom AI and machine learning solutions that help clients automate tedious business processes and develop new opportunities.
Drive down operational costs by up to 30% and take the inefficiencies out of internal processes by automating repetitive tasks and improving quality control with custom machine learning models.
More than 23% of high performers leverage AI and data analytics to diversify their revenue streams. Cash in on the new technologies to identify sizable markets for expansion, forecast demand, and create new products.
Integrate ML into your existing products and services to elevate customer experience, build a competitive advantage, and address old problems with new, unconventional solutions.
As a machine learning consulting company with years of on-the-ground experience in crafting stable, high-performing, and scalable intelligent systems, we step in to guide and support organizations at any phase of ML maturity.
When the ideas are in the air, but you don’t know where to start, our ML consultants take off the burden of sifting through the haystack of unfeasible concepts to find high-impact opportunities.
If you struggle to make ML work hitch-free in production, we fine-tune your ML pipelines, implement solid MLOps practices, and set up an ML governance framework to deliver consistent business value.
AI&ML already power your business operations? There’s always room to enhance the risk-performance-cost ratio. Our ML aces excel in the complex, custom ML system development.
Turn to our AI and machine learning consulting company and get point deliverables geared toward the needs and challenges of your business.
Why is our consultancy different? We find proof first. Our ML consultants estimate the feasibility, usability, and potential of your project. We also define and diagnose the business needs to be achieved with an AI solution and define the right approach to the ML model development.
Our AI and machine learning consulting team runs an assessment of the existing environment, including sizing the available data and discovering the potential for gathering additional data. We also audit data management practices within the company as well as the technologies and tools in use.
Collecting the right data is half the battle for machine learning solutions. Delegate your dataset development strategy to our data science team to get actionable recommendations and valuable insights on the operational range of data, data limitations, major dataset dimensions, and costs of collecting a diverse dataset.
For your ML initiative to be production-ready in fewer training cycles and at a lower infrastructure cost, the data has to go from raw to AI-ready. Machine learning consultancy gives you an early look into our all-encompassing data preparation services. Our data scientists create a data preparation framework tailored to the specifics of your data landscape.
Our team provides a high-level architecture of your ML solution with all the components and integrations involved in building, optimizing, maintaining, and deploying the model. We also match your performance expectations with the optimal feature set and tech stack for machine learning implementation.
Instinctools’ machine learning consultants closely examine your AI solution and the methodology behind its development. We fill you in on the possible model, compliance, and operational risks, including vendor lock-in, tech limitations, and potentially high costs of model training, and offer the ways to take these risks under control. Armed with this insight, we help you manage these risks effectively, keeping your ML journey on track and your costs under control.
With machine learning engineers and data scientists who draw on years of work at the front lines, *instinctools helps you measure and improve the accuracy of your ML project estimates. We assess all the economic nuances integral to AI and machine learning projects. These include the costs associated with assembling and maintaining specialized ML teams, expenditures on dataset markup and updates, equipment expenses, the overhead of using Platform as a Service (PaaS) for neural networks, and more.
A well-executed proof of concept serves as a pivotal decision point, either green-lighting a full-scale deployment or wisely shelving an overly costly venture before it’s too late. Rely on our AI and ML consulting services to develop a small-scale simulation of your solution to prove its technical viability, refine your business model, and evaluate speed, accuracy, scalability, and other trade-offs.
Developing and training a model is not enough – it’s the effective operationalization of that model that truly unlocks its potential. Embracing the best MLOps practices, our machine learning consultants, together with data scientists, build up the framework for organizations to seamlessly integrate AI and machine learning into their core business processes. We help you streamline the entire machine learning lifecycle, from data management to live model operations.
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management
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Live model operations
*instinctools USA
Managing Director, 15
years in IT consulting,
AI Product Owner
Two days with our experts to find personalized solutions for benefiting from AI.
Our machine learning consultants help you cut through the challenges of artificial intelligence and machine learning solutions and address your biggest frustrations to promote smooth AI and ML adoption and foster innovation.
As ML-related obstacles rise, so do AI-based techniques to counter them. If you don’t have any internal data sources, our AI engineers tap into publicly available materials and web scrape a valid dataset. When you have data, but its amount is nowhere near the minimum required for ML model training, we synthesize text, images, audio, video, or tabular data to expand your initial dataset.
ML initiatives are complex to develop as the costs and benefits are harder to predict than for most other IT undertakings, but not for those with experience. With over 50 ML projects in our portfolio, our AI and machine learning consultancy has a well-oiled framework for developing similar AI solutions. We address potential business and technical challenges upfront, giving you a heads-up about the possible lack of training data, preventing non-compliance, and warding off other pitfalls.
While AI and its offshoot solutions do require dedicated investment in terms of skills, talent, and money, you can optimize the development costs by creating a tailored strategy and choosing an optimal tech stack. Our AI and ML consulting firm also guides you through a raft of available pre-trained models and datasets, offering expert advice on how to adapt these resources to your specific needs, thereby enhancing efficiency and reducing infrastructure costs.
The value of AI applications spans both consumer-oriented software and highly complex industrial use cases. ML-based solutions optimize equipment maintenance in the energy sector, simulate building efficiency in construction, and help assess credit risks in banking. Each industry has room for AI and ML revolution, you just need seasoned experts to play your cards right.
The expectations for the quality of the initial product were very high. I think *instinctools did a great job ensuring those expectations are met. We met the developers we were going to be working with and it quickly became apparent that they are very qualified and were able to deliver the vision that we had from our side for the product. They clearly told us what they were going to do, and if there were questions or problems along the way, they clarified them really quickly thanks to transparent communication.
We had a tight delivery deadline and *instinctools has been able to find another developer and assign him to our project from one day to another. And we’ve been able to successfully deliver this project. When the partner is good, things are just getting done. And that was the case with *instinctools.
The quality has been good. It’s been on the expected level: things come on time, we have a good visibility on the things that *instinctools developers are doing and performing for us, communication is good. Wherever we see that we need some more exra resources, we have found *instinctools to be a good partner in helping us out on those areas.
I’ve been impressed by the available skillset, the flexibility to ramp up resources quickly, and the scalability to extend development teams on short notice. I look forward to continue collaboration with *instinctools and their contribution to our projects.
People at *instinctools are quite tech heads, which I like. They have used very advanced libraries, advanced techniques, advanced coding paradigms. So the advantage is that we get reusable code, that we get well-testable code, we get well-maintained code.
The *instinctools team exhibits the flexibility and professionality required for young companies. You can rely on their tested structures and processes that integrate nicely with your internal workflows. Being able to grow your team quickly with experienced professionals that start delivering value immediately and without a long interview process is a huge help. And personally, you will be working with a team of kind and interesting people.
The team is dependable when it comes to managing time and finances, consistently staying within the designated budget. We’re pleased with *instinctools. Their business analysts are exceptional. They serve as the spokespeople between technology and business, representing both sides effectively.
Instinctools is good at understanding the technical issues – once an issue is outlined, they do not need repeated explanation. They also do not simply accept a proposed solution, but they think about it and propose a better solution. I was really impressed by the custom interface they built for us – we outlined the requirements, and they implemented them in a user-friendly way that makes the interface a pleasure to use.
Instinctools does deliver on time and budget. The company proactively asks how they can support our efforts and provide ideas how to help us with very good candidates with expertise that either we requested or that instinctools identified to be missing.
The team demonstrated effective project management, timely delivery, and responsiveness to our needs. They established open communication to facilitate ongoing dialogue and held regular sprint meetings to keep stakeholders informed and engaged throughout the development process.
Instinctools delivered everything on time and was very flexible towards changes in scope during the project work. The team was easy to work with and had a quick response time.
model accuracy
ROI in the first year
data experts in the AI center of excellence
years of client engagement
If you aren’t using ML, you’re missing out. Jumpstart your ML initiative
At *instinctools, we empower organizations like yours to excel in ML solution development. We do that in many ways — from delivering strategic advice to lending the tech edge for AI development. But most importantly, we’re not afraid to roll up our sleeves and tackle any challenge custom AI/ML solutions throw our way.
The failure rate of AI projects is about 92%. That’s why balancing the power of AI requires a holistic approach — there’s no better way to shore up foundational elements for wide-scale AI adoption and net results you are aiming for.
We’ll ask you to provide: business goals and success criteria, access to existing data sources or sample extracts, and a point of contact for domain expertise if you operate in a niche and/or regulatory context. From there, we handle the rest, from data exploration to model deployment and optimization.
Besides offering traditional engagement options like ML staff augmentation, a dedicated team, and an offshore development center, we cater to clients’ need for flexibility with our specialized cooperation model – managed capacity. We’ve designed it specifically to address the highly uncertain conditions of AI and machine learning development, when new models, frameworks, APIs, and tools emerge faster than most teams can responsibly vet – let alone, implement them.
Our data scientists and AI engineers solve any data, model, and compliance-related issues, from enhancing data quality and identifying bias in datasets to addressing model drift, overfitting, and monitoring model computing costs, as well as aligning the ML pipeline with current AI regulations. We also combine the power of advanced natural language processing and speech recognition to build artificial intelligence solutions that understand, interpret, and respond to human language with precision.
You’ll need sufficient storage for an ML-grade dataset (cloud, on-premise, or hybrid), compute resources (on-premise, cloud-based, or hybrid), and infrastructure middleware to manage model training (usually a cloud platform like AWS or Azure; at *instinctools, we have our own technology-agnostic platform – GENE). For production-grade work, add containerization, orchestration, and monitoring tools to the basic setup.
We start with auditing your legacy systems and data flows. After agreeing on the business goals and KPIs, we set up a custom middleware that contains ETL tools, message brokers, API gateways, and other components to seamlessly connect AI and machine learning solutions with your legacy software.
Plan for 1-8 weeks for a solid PoC with clear metrics and a prioritized MVP backlog. Timelines vary with data readiness and scope. Narrow, well-scoped cases with clean data can move faster, while broader or regulated domains may need additional discovery.
