KODAITSU AI
AI that fits your business,
not the other way around.
Four deliberate entry points into AI — from strategy to production. Each is scoped, priced, and time-boxed. No vague roadmaps. No vendor lock-in. Just practical AI engineering that earns trust at each stage.
Week 1 start delivering value
AI Leadership & Strategy
Get senior AI leadership without hiring full-time.
90-day minimum engagement
The common problems:
- AI decisions are made by everyone and owned by no one — efforts are scattered across teams with no clear direction.
- PoCs pass validation but never reach production — the gap between a demo and a feasible product stays open.
- Teams invest in tools and vendors too soon — before defining the business problem and a roadmap.
- Executives demand an AI strategy, but in-house teams lack hands-on expertise to define it.
Strategic Clarity
Actionable AI roadmap with high-ROI use cases and implementation priorities built around your business goals.
Risk Protection
Spot the wrong call before it costs you — architecture decisions, vendor engagements, and project priorities.
Niche Expertise
Senior AI leadership to overcome the 95% failure rate of AI pilots, driving higher revenue growth.
Governance & Accountability
Clear AI ownership, measurable outcomes, and executive-level workflow control.
| Full-time hire | Fractional AI Leadership | |
|---|---|---|
| Time to start | 4–9 months | Week 1 |
| Costs | $200K–$1M/year | Fraction of the cost |
| Commitment | Long-term | Flexible (90+ days) |
| Expertise | Depends on hire | Certified senior experts |
| Risk | High | Low |
2–4 hour interactive workshop · 2 weeks end-to-end delivery
Bright AI Sessions
Hands-on workshop to identify the right use cases for your business.
Fixed cost: $2,500–$5,000
The common problems:
- Without a defined focus, AI efforts spread thin across the organization and deliver nothing.
- A long list of potential AI initiatives keeps growing — but without a way to evaluate them against each other, nothing gets prioritized.
- Data and ideas are scattered, making it hard to define real use cases. Without structure, neither turns into something you can build on.
- Engineering teams can't scope what hasn't been defined. Executives won't fund what hasn't been validated. Both sides stay stuck.
AI Opportunity Map
A focused set of AI use cases built around your business context, your data, and your team's capacity.
Prioritized Roadmap
Ranked list of initiatives with clear next steps, sequenced by impact and effort.
Feasibility & ROI Assessment
Understand exactly which projects are realistic, what they will cost, and what they need to return.
Prototype Blueprint
High-level architecture, defined validation criteria, and a specific implementation approach your team can act on day one.
| Without Bright AI Session | With Bright AI Session | |
|---|---|---|
| Direction | No clear starting point | Structured approach immediately |
| Initiatives | Multiple ideas, no validation | Use cases evaluated against your business |
| Investment Risk | High – no proof before investment | Low – risks identified upfront |
| Decision Speed | Delayed by uncertainty | Faster jump to execution with approved plan |
2–4 week audit duration
Data Audit
Assess if your data is ready for AI before investing in development.
C-level data & AI experts · zero vendor lock-in
The common problems:
- When data lives in silos, spreadsheets, and disconnected systems, AI models have nothing reliable to learn from.
- Compliance gaps, security vulnerabilities, and data quality issues rarely surface during planning — teams often spot them in production.
- Most teams don't know what's missing until development starts. By then, the budget is gone and the timeline is broken.
- Committing to AI without validating data readiness puts your entire architecture at risk.
Data Readiness Assessment
Expert evaluation of your current data situation — what you have and whether it can support the AI use cases you're planning.
Actionable Roadmap
Detailed plan from where your data is to where it needs to be. Every step is scoped, sequenced, and ready to act on.
Gap Identification
Deep look into data quality, structure, availability, and governance. You'll know exactly what's missing before development.
Risk & Compliance Review
Identify security, privacy, and regulatory gaps before they become the reason your project stalls. Essential for regulated industries.
| Without Data Audit | With Data Audit | |
|---|---|---|
| Project kick-off | Start building blindly | Clear understanding of data setup |
| Data Issues | Surface mid-development | Identified and addressed first |
| Delivery | Delays, rework, and budget overruns | Faster, more predictable, fewer surprises |
| AI Outcome | High risk of project failure | Higher success rate, shorter path to production |
8–10 weeks from kickoff to delivery
Proof of Concept
Prove AI feasibility before you scale.
Working demo · low risk · validate before scaling
The common problems:
- Teams commit budget to AI concepts before the idea has been tested for feasibility, business impact, and ROI.
- Without a structured validation phase, you have no reliable basis for what the system will deliver and when.
- Companies push toward full-scale development before validating the solution in a real environment.
- Late discovery of business misalignment and potential risks often exceeds the planned investment.
Working AI Solution
A functional model or automation built on your data, scoped to your use case, and tested by your team before any decision to scale.
Technical Validation
Validate architecture, scalability, and security against your production requirements before they become blockers.
Feasibility & ROI Validation
Identify what your solution can realistically deliver and whether it justifies the investment.
Clear Path to MVP
Actionable roadmap and investment plan to move from validated PoC to production-ready product in 12–16 weeks.
| Without PoC | With PoC | |
|---|---|---|
| Project kick-off | Full investment committed before anything is proven | Feasibility and ROI validated before the budget scales |
| Clarity | Unclear business impact until deep into development | A working solution that shows exactly what AI can deliver |
| Risk | High – failure pops up late and costs more to fix | Low – gaps identified and resolved before scaling |
| Delivery | Long, expensive cycles with unpredictable outcomes | A defined, confident path from validation to production |
Tailored for enterprises and startups.
Different organizations need different AI engagements. We structure everything around your reality — not a one-size-fits-all methodology.
For Enterprises
Plan with confidence
Strategic Alignment & Readiness
- AI Roadmapping & Readiness Audits — Assess systems, data, and priorities.
- Fractional AI Leadership — Experienced AI advisors and decision-makers.
- AI Discovery Workshops (2–4 hrs) — Align stakeholders, surface high-value opportunities.
Smarter processes, measurable gains
Intelligent Operations & Automation
- Intelligent Automation & Adaptive Workflows — Streamline operations, support, and compliance.
- Internal Knowledge Assistants — Unlock internal data for faster, better decisions.
- RPA Modernization — Upgrade legacy RPA to AI-driven Agentic Automation.
De-risk innovation, accelerate adoption
Experimentation & Delivery Pathways
- PoC Execution (6–10 weeks) — Validate feasibility, data readiness, and ROI.
- MVP Build & Delivery (12–16 weeks) — From prototype to production-grade systems.
- Continuous Optimization — Iteratively improve models post-launch.
Scale with the right expertise
Talent & Capability Expansion
- Team Expansion & Staff Augmentation — Add AI/ML engineers, data scientists.
- Specialized Expertise on Demand — Niche skills for critical phases.
- Long-Term Partnership — Flexible resourcing that grows with your roadmap.
For Startups
Senior expertise, zero overhead
Plug-In AI Leadership
- Flexible access to AI and product leaders without permanent headcount.
- Strategic guidance across product direction, technical execution, and investor communications.
- Close critical leadership gaps while reducing risk and accelerating growth.
Clarity before commitment
High-Value Outcomes
- Short, focused sessions to surface AI-driven product features or models.
- Structured framework for aligning stakeholders on high-impact opportunities.
- Low-risk way to prioritize limited resources effectively.
Validation that wins funding
PoCs That Attract Investors
- Rapid prototypes that prove feasibility and market potential.
- Fast, cost-efficient testing of assumptions to reduce startup risk.
- Evidence-backed outcomes that strengthen fundraising and roadmap decisions.
Built for adoption and growth
MVPs Designed to Scale
- End-to-end development of production-ready AI features.
- Integrated MVPs designed for scalability and early adoption.
- Launch-ready solutions that build investor confidence and accelerate traction.
Defensible choices for founders
Aligning Tech, Strategy, and Funding
- Advisory to align technology with long-term product strategy.
- Informed guidance on model selection, tech stack, and investor narratives.
- Support to make investor-ready, defensible decisions.
Talent when you need it
Flexible AI Teams to Accelerate Growth
- On-demand access to AI, ML, and Data Science specialists.
- Flexible support for MVP scaling, early-stage builds, or demand spikes.
- Cost-efficient progress without long-term hiring commitments.
Svitla AI in action.
Not sure where to begin? Start with these key use cases.
AI & ML · Hospitality
AI-Enhanced Hospitality Data Platform
AI-driven digital transformation for a leading hospitality analytics provider — advanced search, precise demand forecasting, and innovative data extraction.
Big Data & IoT · Retail, Hi-Tech
Automation for Drone Data Analysis
Automated information system for a global conglomerate — microservices architecture on AWS, streamlining data analysis from drone-captured media.
Cybersecurity · DX
Digital Identity Security Solution
Enhanced online security leader's digital identity solutions — optimized consumer identification, system performance, and UI/UX across web and mobile apps.
Proven engineering that powers AI ambitions.
Leading enterprises don't choose us just for AI expertise — they choose us for the track record in complex application delivery, secure enterprise platforms, and large-scale integrations.
IAOP
Global Outsourcing 100 — 2025
AWS
Advanced Consulting Partner
SOC 2
Security Certified
ISO 9001
Quality Management
Not sure where to start?
Most teams don't need a full AI transformation — they need a clear first step. Book a free 30-minute consultation and we'll help you figure out which entry point fits.