I’m Ivan Pohrebniyak, Chief Delivery Officer at Master of Code Global, where I’ve spent the last six years helping companies, from banks and insurers to healthcare networks and auto dealers, operationalize AI effectively.
One thing we hear often: “Are you a platform?”
We’re not. But we use them. And it is our advantage to be able to tailor a solution rather than being platform-features-locked.
In some cases, clients come to us needing to extend or fix something they’ve already built on a platform. In others, they’re starting fresh, and what they need is a solution tailored from the ground up. Either way, our role stays the same: shape the right approach, fill the gaps, and deliver an application that performs in your business ecosystem, not someone else’s.
I wrote this article to unpack how we do that.
You’ll see:
- 3 most common paths companies take to implement AI and what makes each succeed (or stall).
- How our team gets involved, depending on your stage, stack, or strategy.
- What real business impact looks like when you align delivery with real-world constraints.
If you’re a business leader asking, “Where do we start with AI implementation?” or “Why isn’t our AI working the way we wanted it?”, this guide is for you.
Table of Contents
What AI Success Really Looks Like—3 Clients, 3 Strategies
If building an AI solution was a strategy game, your first move would be choosing how to play:
- Do you pick a ready-made character and rush into the action?
- Spend time engineering your own from scratch, fine-tuning every detail?
- Or combine strengths from both paths?
Below are stories from our actual clients. While we can’t share names due to NDAs, each scenario shows a different path and the results you achieve with the right approach.
1. The Startup That Chose Speed
A regional digital services startup came to us looking for a fast, cost-effective solution to handle FAQs and capture leads, ideally within a $10,000 budget. Their team was small, and time-to-launch was a priority.
We recommended one of our platform partners. Using its AI studio, they built and launched a bilingual chatbot in just two weeks. It started capturing leads right away and checked every box for that initial phase—minimal lift, quick impact.
Now that the basics are running, they’re exploring what comes next. Improving the native feel of the language, refining the tone, and adding better control over hallucinations are all on the table. But some of those enhancements bump against the platform’s limitations, pushing the team to consider a custom layer for greater flexibility down the road.
2. The Legacy Leader Who Went All-In on Custom
A global professional association built a strong reputation over five decades, but their support systems haven’t kept up. Legacy tools, long wait times, and impersonal interactions were falling short of what their members expected.
We helped them to build a fully custom AI-powered support system, from messaging channels to automation, routing, and GenAI agent tools, tailored to their workflows, voice, and international reach.
Key outcomes:
- 25% increase in digital chat usage
- Over 1.5 million chatbot interactions
- Escalations dropped thanks to GenAI-enhanced intent recognition
The custom route required more time and investment, but now they have a flexible, scalable, and intelligent support system designed around their business, not someone else’s templates.
Our client serves a global customer base including countries that don’t speak English natively. Their traditional Natural Language Understanding (NLU) often struggled to accurately decipher customers’ Intent due to inconsistencies in grammar or spelling, resulting in higher escalations to human agents. We drastically decreased escalations by creating a “hybrid” experience, in which we augmented the NLU by integrating the power of Generative AI & a Large Language Model, which was significantly better at understanding customers.
3. The Luxury Brand That Designed for Impact
The fashion consignment leader had a bold ask: could a virtual assistant deliver the same level of trust, elegance, and security that their customers expect in-store, online? They wanted a solution that could negotiate with buyers, assist consignors, and route VIPs to the right agents flawlessly.
Our team empowered them to strike the balance: start with a proven platform, then layer in exactly what made the experience premium. Silent close, auto-resume, VIP pod routing, fraud filtering, personalized codes.
Results:
- 89% average CSAT
- 91% first contact resolution rate for an agent group
- 8 custom features integrated into an enterprise-grade flow
This wasn’t about speed or control; it was about designing for what matters. And that made all the difference.
So… Which Path Is Right for You?
Each of the companies we just explored made a strategic call. One chose speed. Another went all-in on control. And the third, balanced both for long-term flexibility.
None of these choices is inherently wrong, but each comes with trade-offs. The key is making a decision that fits your short- and long-term reality.
What I’ve learned over the past two decades is that success usually hinges on three things:
- The complexity of your use case(s);
- The maturity of your organization, internal teams, and tech stack;
- The resources you’re ready to invest.
Get that alignment right, and everything else starts falling into place. But how do you actually get there?
Also see: How Much Does AI Cost? Demystifying the Variables that Influence Pricing
How We Build AI Around Your Particular Business Needs
You don’t need all the answers before you start. Master of Code Global steps in to help you align on use cases, validate your readiness, and move forward with clarity – whether it’s an upgrade or a net-new build.
We’re platform-agnostic experts. Our job is to engineer feature‑optimum and cost‑optimum solutions using the tools, platforms, and models that best fit your compliance, security, infrastructure, user journey, and business case needs.
That mindset has guided us since 2004. Unlike vendors tied to a specific platform or pre-set architecture, we begin with a single question: What do you actually need, and how will you measure the success of your business case implementation?
From there, we design everything else, that is, the architecture, timelines, team structure, analytics, etc. That’s why we don’t push a one-size-fits-all solution. We’re not vendor-locked. We build holistic systems shaped by your goals, not platform limitations.
Sometimes we guide clients in building on top of these platforms. Other times, we help extend them with the add-on features that are missing. And in some cases, we build an entirely custom solution from scratch, aiming to leverage as many ready to go solutions/components.
The truth is, no platform covers every business case perfectly. As our Director of Pre-Sales Strategy & Delivery, Olga Hrom, puts it:
There’s still this idea that using a platform is a plug-and-play game. You connect a knowledge base, add some built-in AI, and it’s done. But the reality is, there’s a lot of hidden complexity, and that’s where most projects fall short if not handled properly.
That complexity might show up as rigid analytics, limited LLM visibility, integration challenges, or user experience gaps. Our role is to close those gaps – whether that implies custom connectors, LLM benchmarking, conversation redesign, or full program support.
More often than not, companies reach out to us after launching an assistant that falls just short of expectations. As Olga explains:
“We run audits, then we refine the full experience. That means conversation design, user journey flows, bot persona, tone of voice, and even rewriting prompts from scratch. It’s a full-cycle rebuild, not just a “quick” patch.“
Here’s what we focus on to get it right:
Business-first architecture
We begin by mapping out your operational goals, constraints, scalability expectations, and KPIs. From there, we design an architecture that fits your real needs, whether that involves building from scratch or layering on top of existing tools.
Vendor-neutral expertise
Master of Code Global has built and extended solutions across 20+ enterprise AI platforms and cloud environments. As certified partners with Google Cloud, Salesforce, and AWS and strategic allies of Sinch, Cohere, Snaps, Infobip, Chatfuel, LivePerson, Verint, Vonage, Voiceflow, Ada, Boost.ai, HumanFirst, Glia, BotPress, Quiq, Nylas, and others, we understand the ecosystem inside and out. We use that knowledge to recommend the best-fit option for your goals.
At Master of Code Global, we take a fundamentally different approach than platforms. There’s this vendor lock-in mentality where platforms will only outline what’s possible within their limitations and try to fit your business requirements into their capabilities. We do the opposite—we start with your business case and fit the right technology to your requirements. The reality is that in most cases, out-of-the-box connections simply don’t work. Every business has different systems, and all these connectors need custom development. We’re not vendor-locked, so we can recommend the best combination of technologies for your specific situation rather than forcing you into a single platform’s constraints.
Tactical validation over assumptions
Our best process typically begins with a focused Discovery and Proof of Concept phase. This allows you to test real use cases, assess infrastructure gaps, and clarify expectations before making larger investments. In most circumstances, it helps our clients reduce development waste by 50–70% or even, in some rare cases, validate for themselves that they are not ready yet internally to go ahead with the anticipated full implementation scope.
I recall the time, some 5 years back, when a large energy utility provider wanting to fully automate their internal HR process for 20,000+ employees via a chatbot/virtual assistant. Thanks to our discovery work, we soon identified that their HR system and processes were not yet ready to be handled by AI.
Planning an AI PoC? Here is what our Director of Pre-Sales Strategy & Delivery Says You’re Missing
Scalable delivery accelerators
Our proprietary LOFT framework reduces setup time by 43%, cuts pre-MVP costs by up to 20%, and decreases support workload threefold. It is built to help you move from prototype to production with speed, while still maintaining adaptability.
Integration where it matters most
Most solutions break down at the integration layer. We solve that by designing and delivering connectors for platforms, payment gateways, proprietary CRMs, and other systems critical to your workflow. Where out-of-the-box fails, we make it work.
Full-cycle implementation, not just development
We take responsibility for the entire delivery lifecycle. That includes user journey design, tone of voice, conversation modeling, prompt optimization, compliance guardrails, analytics configuration, post-launch business results review/monitoring, and solution tuning. It’s not about delivering code, it’s about delivering a complete, working solution.
Programs, not just projects
Our team treats every engagement as part of a larger program, not a one-off build. That means ongoing support for audits, rebuilds, migrations, and phased scaling.
Where You Are, What You Need, How We Help
Most of our clients aren’t starting from scratch. They’ve already tried something or are under pressure to act fast. That’s why our work begins with understanding where you are and where the friction lies.
These examples reflect the problems we’re trusted to solve.
- Not sure how to get started with AI? Our team steps in to identify high-impact use cases, assess data readiness, and define the right tech stack. The outcome: a prioritized roadmap, effort estimates, and clear next steps.
- Your bot can’t connect to the systems that matter. Custom connectors are developed for your CRM, ERP, or proprietary tools, so your assistant can do more than talk.
- Already launched an AI assistant, but it’s underperforming? Master of Code Global conducts a full audit of your current setup, from flow logic, UX, and tone to a technical implementation review. If it’s not salvageable, we design and rebuild what’s needed, on your stack or ours.
- Need to prove value fast to keep the AI budget? A focused Proof of Concept is delivered using your real data and goals. Small scope, big insight before scaling.
- Your customer bot works fine, but internal teams still struggle. That’s where we create GenAI agents tailored for internal workflows and layer in dashboards for actionable insights. No need to change your current setup.
- Looking to launch across multiple channels and languages? We architect omnichannel bots that work across Apple Messages for Business, Google RCS Business Messaging, Web, and more, tailored for each market, with compliance and tone built in.
- Realized your platform choice isn’t the best fit? Migration is handled end-to-end: rebuilding prompts, redesigning flows, and integrating with your backend so your team isn’t starting from scratch.
- Bot works, but sounds like a bot? Conversation Design specialists refine it: from persona to tone to flow. It still automates, but with a human touch.
- Working in a regulated space? Our AI design process incorporates security and compliance from day one. From HIPAA to GDPR to AML, it’s built into the system, not just policy docs.
- Scaling and need a long-term team? We embed a dedicated squad into your organization, including software developers/engineers, ML engineers, conversation designers, AI Trainers, QA engineers, etc. Flexible terms, ready to scale with you.
- Just know you “need AI” but don’t know how? We’ll help you figure it out. From first use case to multi-phase rollout, we guide your journey end-to-end.
No matter what brought you here, an AI assistant that isn’t pulling its weight, a compliance blocker, or pressure to “do something with GenAI – we’ve probably solved it before.
Our job is to meet you where you are, cut through platform noise, and deliver a system that works for your business long after the launch day.
Let’s talk through your use case and get on clear, possible next steps for your business.