AI consulting that goes beyond advice

Problem definition before design

Most teams start with a tool or a model. That’s the mistake.

Consulting forces a clear definition of:

  • What task is being improved
  • What “good” looks like
  • Where AI is actually needed (and where it isn’t)

Early validation on real data

Ideas sound good in workshops. They break on real inputs.

Consulting introduces fast, controlled validation:

  • Testing on actual datasets
  • Checking edge cases early
  • Identifying where models fail before scaling

Feasibility grounded in systems

A working demo is not a deployable solution.

Consulting connects AI ideas to real constraints:

  • System integration
  • Data availability and quality
  • Latency, cost, and maintenance consideration

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Artificial intelligence consulting services

AI strategy

Define a clear roadmap for AI adoption:

  • Identify business processes and workflows that can benefit from AI
  • Map AI opportunities to measurable outcomes and business objectives
  • Design a customized AI implementation plan with milestones and priorities

Business case analysis

Turn potential use cases into actionable projects:

  • Break down high-level business goals into concrete, actionable processes
  • Segment and prepare data for AI model training and validation
  • Evaluate cost-benefit balance, ROI potential, and resource requirements

Solution optimization

Maximize the impact of existing AI initiatives:

  • Analyze current AI use cases, models, and technology stack for performance gaps
  • Identify bottlenecks and improvement areas to enhance results
  • Optimize models, data workflows, and system architecture to increase value and efficiency

AI readiness assessment

Evaluate the current state of AI preparedness across people, processes, and technology:

  • Analyze data quality, availability, and completeness for AI use cases
  • Audit IT infrastructure for scalability, security, and AI compatibility
  • Assess technical skills of teams and identify knowledge gaps
  • Review legal, regulatory, and ethical considerations for AI adoption
  • Highlight bottlenecks and prioritize areas for actionable improvement

AI development

Obtain robust technical foundations for AI projects:

  • Choose the optimal AI frameworks, platforms, and toolkits
  • Select tools specifically suited for Generative AI development
  • Model total cost of ownership and resource requirements
  • Plan for modular, future-proof system design

AI integration

Embed AI seamlessly into existing systems and workflows:

  • Define data pipelines, storage, and preprocessing requirements
  • Plan interoperability with legacy systems and external APIs
  • Choose processing patterns: batch, streaming, or real-time
  • Map integration points to minimize operational disruption
  • Provide guidelines for monitoring, logging, and failover strategies

Alexey Karankevich

Alexey Karankevich

AI Innovation Lead

An MITx MicroMasters graduate in Data Science, Alexey leads R&D with hands-on AI expertise. He has driven key innovations, including a social media analytics startup and a $10M health AI project heading to EU clinical trials.

Yariv Z Levy

Yariv Z. Levy

AI Strategy Advisor

With a PhD in AI from UMass Amherst and a Master’s in Computer Science from EPFL, Yariv bridges AI and business impact. He has collaborated with global leaders like Nestlé and Roche and founded his own AI consultancy boutique.

Discover the full team driving Oxagile’s AI consulting services.

The power of structured AI guidance

According to RAND (2025), over 80% of AI projects fail – not because of models, but due to poor framing, unclear scope, and weak validation. Working with an AI consulting firm helps avoid that.

“I thought a chatbot would fix everything”

Teams often start with a tool in mind without clearly defining the actual problem.

Insight: Early validation matters

The solution isn’t always a complex AI model. By analyzing the workflow first, simpler adjustments, like restructuring data or adding lightweight support layers, can deliver faster results with less risk.

“It worked in the demo, but not on our files”

Models often shine in controlled tests but struggle with real-world data and messy inputs.

Insight: Test early, test real

Validating on actual datasets and edge cases identifies where models might fail, guiding hybrid approaches or preprocessing to prevent wasted development and ensure practical usability.

“We built it, but it won’t scale”

Prototypes often don’t consider infrastructure limits, latency, or maintainability.

Insight: Check feasibility early

Assessing deployment requirements and system constraints upfront avoids bottlenecks and facilitates AI solutions being integrated sustainably into existing workflows.

“Too many features, too soon”

Teams frequently attempt to automate everything at once, slowing delivery and increasing complexity.

Insight: Prioritize high-impact areas

Focusing on the most valuable tasks first provides tangible results quickly, reduces unnecessary complexity, and sets the stage for incremental expansion.

Unsure where AI can make an impact?

Begin with a guided session with an artificial intelligence consulting company
to define the most promising path forward.

Choose the next step for your AI initiative

AI projects vary in scope and complexity. Structured AI consulting gives you the expertise to explore ideas, test workflows, and plan deployment effectively.

Explore our approach

Learn how engineering teams design, prototype, and refine complex AI workflows, providing solutions that are scalable, reliable, and aligned with your goals.

Tackle advanced engineering

Dive into how complex AI systems are designed, tested, and refined. See how experimental workflows, prototypes, and research-driven methods translate into practical solutions.

Experiment with agentic AI

Work alongside engineers to design and test autonomous AI systems that explore novel workflows and tackle complex, adaptive challenges.

Adopt ready-to-use solutions

Leverage prebuilt AI systems, like Voiager, to accelerate deployment for voice interaction or workflow automation without starting from scratch.

Industry-specific AI consulting


Video and streaming

With 20+ years powering online video, our enterprise AI strategy enhances recommendation engines, adaptive pipelines, and content moderation.


AdTech

Decades of AdTech insight turn complex DSPs, SSPs, and retail media data into actionable strategies, improving targeting, campaign performance, and ROI.


EdTech

AI-driven personalization and adaptive assessments create scalable, data-informed learning platforms that help students, educators, and institutions.


Transportation

Predictive routing, demand forecasting, and fleet optimization solutions make logistics operations more efficient, using real-time IoT and operational data.


Finance

AI models for fraud detection, risk scoring, and automated trading deliver compliant, real-time insights for high-volume financial workflows.


Healthcare

Telemedicine and patient monitoring platforms transform device and EHR data into secure, actionable insights, supporting better outcomes.

AI expertise across key technologies

Computer vision

Computer vision

AI-powered visual intelligence for images and video, including object and facial recognition, real-time monitoring, and video analytics.

Applied across online video, AdTech, public safety, and industrial workflows, using deep learning frameworks and cloud or edge deployments.

Big data

Big data

We design and manage secure data pipelines and analytics ecosystems, delivering real-time and batch insights across video, AdTech, eLearning, finance, and more.

Our enterprise AI consulting services include ETL/ELT development, data migration, quality management, visualization, and AI/ML integration.

Generative AI

Generative AI

Building and integrating GenAI solutions that transform workflows, from data preparation and model adaptation to deployment in chatbots, virtual assistants, and industry-specific applications. Applied across video streaming, AdTech, retail, healthcare, and Fintech.

Large language models (LLMs)

Large language models (LLMs)

We develop and deploy LLM-powered solutions for chatbots, search, and analytics. Our team brings hands-on expertise in prompt engineering, model selection, and fine-tuning, with practical experience integrating large language models into enterprise workflows and products.

FAQ

What does a typical AI consulting engagement with Oxagile look like?

AI strategy consulting services start with understanding your business goals and challenges, followed by evaluating technical feasibility, designing an actionable roadmap, and delivering a tailored AI solution. As an AI technology consulting company, we combine strategy, R&D, and engineering to secure practical, measurable results.

We have an idea for an AI feature but aren't sure if it's technically feasible. Can you help?

Absolutely. Our team applies AI project development and consulting to assess feasibility early, examining data requirements, system constraints, and model suitability. This helps you avoid costly dead-ends and focus on solutions that can actually be implemented.

How do you provide the security and privacy of our proprietary data?

Data security and privacy are core to our process. We follow strict protocols, including encrypted storage, access controls, and compliance with industry standards, ensuring sensitive information is fully protected throughout development.

Who owns the intellectual property (IP) of the AI models developed?

You retain full ownership of the AI solutions we develop. Oxagile delivers models, code, and documentation, giving you complete control over the IP and the ability to scale, adapt, or maintain the system independently.

Can you help us integrate Generative AI (LLMs, ChatGPT, etc.) into our existing software?

Yes. We guide integration of LLMs and other Generative AI tools into your workflows, ensuring seamless connectivity, optimal performance, and alignment with your business processes.

How long does it take to build an AI Proof of Concept (PoC)?

A PoC timeline depends on complexity and data availability, but we typically deliver results within a few weeks, providing early validation, insights, and guidance for full-scale implementation.

What industries benefit from AI consulting?

Enterprise AI consulting services can provide value across nearly all sectors, from finance, healthcare, and e-commerce to media, education, and industrial automation. Organizations that manage large datasets, complex workflows, or customer-facing operations can benefit especially from strategic AI guidance, as consultants help identify high-value use cases, optimize processes, and implement AI responsibly.

Let’s chart your AI path

Move beyond trial-and-error. We can help identify high-priority projects, align resources, and gain a strategy grounded in real-world data.

Schedule a session