Kodevent

Where is your AI project today?

Pick the one that sounds like you. We'll show you what we'd do first, how long it takes, and a project where we've already done it.

AI consulting & strategy We have ideas, but no clear plan You know AI could help, but not where it pays off or whether your data is ready. Show me the plan Custom AI & LLM development We know what we want to build You have a use case or product in mind and need a team to ship it to production. Show me the plan AI team augmentation We need AI engineers on our team Your roadmap is set, but you're missing ML, LLM, or MLOps skills and can't hire fast enough. Show me the plan

Your path: AI consulting & strategy

Find where AI pays off, then prove it with a working prototype

We work with your team to pick the use cases worth doing, check your data, and validate the best one on real data before you commit to a full build.

  1. Week 1

    Discovery workshop

    We map business goals to AI opportunities with your domain experts - in business language, not jargon.

  2. Weeks 1–2

    Feasibility & data readiness

    We assess your data and infrastructure and rank use cases by value and effort.

  3. Weeks 2–4

    Roadmap & proof of concept

    You get a roadmap with short- and long-term milestones, and a lean prototype tested on your data.

  4. Then

    Your call

    Build with us, extend your own team, or take the roadmap in-house.

Plan my AI strategy

What you walk away with

  • Validated AI opportunities, ranked by ROI
  • Data and infrastructure readiness assessment
  • Roadmap with short- and long-term milestones
  • Responsible AI and governance guidelines
$500K+
saved per year in fleet maintenance

For FleetIQ, use-case mapping pointed to predictive maintenance. The model now flags failures early, cutting unplanned downtime by 40%.

Logistics · Machine learning on sensor data and repair logs

Your path: Custom AI & LLM development

From use case to production AI, with a prototype in 3–4 weeks

One accountable team handles modeling, engineering, UX, and deployment - generative AI, LLM apps, and ML models that plug into your CRM, ERP, and internal tools.

  1. Weeks 1–4

    Prototype on your data

    We build a lean prototype and test it against real data to validate the idea and cut risk early.

  2. Next

    Model development & integration

    We train, tune, or fine-tune models - GPT, Claude, or open-source with RAG - and connect them to your systems.

  3. Launch

    Deploy

    APIs, cloud endpoints, or edge devices, with explainability and human-in-the-loop checks where needed.

  4. Ongoing

    Monitor & improve

    Retraining, drift monitoring, and A/B tests keep accuracy up as your data changes.

Get a build proposal

What we build

  • AI assistants, chatbots, and agents
  • Document processing, summarization, and OCR
  • Predictive models, forecasting, and anomaly detection
  • Recommendation and personalization engines
70%
of support queries resolved automatically

A conversational AI assistant for a global e-commerce client that also cut support costs by 40% and lifted satisfaction scores by 25%.

eCommerce · 6 engineers · Python, OpenAI API, TensorFlow, AWS

Your path: AI team augmentation

Vetted AI engineers working in your sprints within 2–4 weeks

Skip months of hiring. Our specialists join your tools, rituals, and pipeline, on flexible contracts you can scale up or down.

  1. Day 1

    Tell us the gap

    We review your roadmap and suggest the right team structure for your use case.

  2. Within days

    Shortlist of candidates

    You get pre-screened profiles and interview whoever you like.

  3. Weeks 2–4

    Onboarding

    We handle contracts and help integrate engineers into your workflows and agile cycles.

  4. Ongoing

    Backed by our AI leads

    Our practice leads stay available for hands-on support and reviews.

Find me AI engineers

Roles we place

  • AI / ML engineers
  • LLM and GenAI specialists (fine-tuning, RAG)
  • Data scientists (NLP, vision, forecasting)
  • MLOps engineers
75%
of our 180+ engineers are mid- or senior-level

Every engineer passes a selection process for computer science depth, analytical rigor, and business awareness - so they contribute without hand-holding.

English-proficient · Overlap with US and EU hours

Results from AI we've shipped

Measured in production, after launch.

ResultProjectIndustry
70%of support queries resolved by an AI assistantSupport costs down 40%, satisfaction up 25%eCommerce
60%less time reviewing legal documentsGenerative AI summarization with domain fine-tuned modelsLegal tech
48%higher engagement with FinSightPersonalized financial insights; session time up 60%+Fintech
40%less unplanned downtime with FleetIQPredictive maintenance saving $500K+ a yearLogistics
40%faster provider response with PulseNLP triage of patient symptoms via chatHealthcare
22%sales lift from ShopWise recommendationsReal-time suggestions across web and mobileRetail
180+engineers and AI experts
150,000+engineering hours in AI and software
96%client satisfaction
ISO 27001certified, NDA before any details
We build withOpenAIAnthropicAWSGoogle CloudMicrosoft AzureSnowflake

Tell us what you want to build

You'll get a tailored plan within one business day. No obligation.

  1. Discovery callWe learn your goals. NDA first if you need it.
  2. Proposal or shortlistScope, timeline, team, and cost - or pre-screened engineers within days.
  3. KickoffWork starts within 7–10 business days of contract approval.
Mikhail Aksionchyk
Mikhail AksionchykHead of Executive Operations · LinkedIn

We reply within one business day.

Before you reach out

Which AI models do you work with?

GPT, Claude, and open-source or fine-tuned custom LLMs, built with PyTorch, TensorFlow, Hugging Face, and LangChain. We pick what fits your latency, cost, and data-handling needs.

How does pricing work?

It depends on scope. After the assessment you get a proposal with team, timeline, and cost, with no obligation. Project work usually runs on time and materials, so you pay only for what's used.

Can we switch paths later?

Yes. Many clients start with strategy, move into a build, then keep a few engineers embedded in their team. The same people can stay with you throughout.

Where are your engineers based?

We're US-headquartered with development hubs in Poland, Georgia, and Uzbekistan, overlapping with both US and European business hours.