Marina Rakhimzhanova · AI + Human Lab
We help businesses win customers, earn repeat purchases and enter new markets. We connect strategy, customer experience and AI, then test what changes in sales, economics and the way teams work.
For investors and strategic partnersProjects in focus
01 / WHY
Enquiries fail to turn into payments. Customers do not return. Revenue grows, but profit does not. Before adding another tool, we find the source of the loss and choose the first change worth testing.
We do not start with technology. We start where a customer or a business loses time, money, trust, or an opportunity to grow.
01You need a clear starting point
02You have a specific idea to test
02 / GRI × GTM GROWTH SYSTEM
We find where your business loses customers, sales and cash. We design a solution around your product, audience and market, using AI to test ideas faster, improve the customer experience and understand the economics of growth.
AIStart360 methodology · Marina Rakhimzhanova ↗We establish your baseline, agree on a goal and choose the lever with the greatest potential. Then we test the change, measure the result and build on what works.
AIStart360 PUBLIC LAB / CUSTOMER GROWTH LOOP
Winning a customer is only the beginning. We design an experience that delivers value early, gives people a real reason to return and helps them get more from your product. Customer experience, sales and unit economics work as one system.
The customer understands which job your product solves.
UX Research · performance
The team completes a first useful work task.
UI/UX tests · first value
The solution becomes part of the normal workflow.
CJM · behavioural triggers
The customer buys again or renews a contract.
CRM segmentation · A/B tests
Another team uses your product to solve its own job.
AI personalisation · bundles
For your product, we agree channels, segments, events and periods. We assess 30/60/90-day retention once the relevant cohort has matured; 21 days do not replace 90 days of observation.
Clicks and activity are not enough. Before a test, we define a useful customer action, a business metric and a comparison method. Afterwards, we account for costs and decide what to do next.
The customer takes a meaningful next step.
The customer achieves an outcome, not merely opens the product.
The cohort returns to a useful activity.
There is a new payment, not just another visit.
Customer contribution grows after costs and rewards.
Returning to a product and paying again are different outcomes. We measure both and relate them to a genuine customer need.
Customer signal → Hypothesis → Human × AI pilot → Cohort evidence → Economics → Decision
Before launch, we define a metric, timeframe and success rule. We compare with a control or similar group and account for seasonality, discounts, returns, team time and AI costs. Timing alone does not prove an AI effect.
We track CAC, conversion, 30/60/90-day retention, repeat rate, AOV and LTV by channel, segment and cohort. We agree the event, period and costs before launch. We distinguish projected LTV from realised contribution; for long cycles, observation continues after Bootcamp.
Evidence supports the effect, with acceptable economics and quality.
There is a signal, but evidence or economics are not yet sufficient.
The decision rule is not met or guardrails are breached.
We communicate with customer consent and make opting out easy. Targets are benchmarks, not growth guarantees.
UX Research · CJM · User Journey Mapping · UI/UX testing · A/B testing · behavioural triggers · CRM segmentation · AI personalisation · performance marketing · upsell · cross-sell · bundles
HONOR’s customer journey provides context for a Customer Lifecycle hypothesis, not proof of this model’s impact.
03 / IMPLEMENTED CASE
See how the website, CRM, inventory and loyalty system work together. Implemented features, owner-reported figures and modelled scenarios are clearly distinguished.
Implemented · all described modules · owner confirmed
How product choice, ordering, team workflows and loyalty can form one customer journey. This case explains the implemented website, CRM and inventory system, their roles and the limits of the evidence.
Our role with HONOR Group is AI Growth Digital Partner. We work on the AIStart360 platform.
04 / METHOD
From a clear challenge to a solution we can test. At every stage, you know what we are doing, what you will receive and what evidence supports the next step.
We identify where performance breaks down: in the product, customer decision, sales process, operations or team.
We choose the main constraint and turn the GRI findings into a practical action plan.
We run a focused change and compare its performance with the existing process.
We embed a successful approach in processes, responsibilities and metrics so the team can repeat it.
Timings are planning guides. Scope, metrics and team involvement are agreed before starting. Each phase informs the decision to proceed.
Where does the customer or business lose value?
Journey, data, constraints, and baseline metrics.
What does AI do, and what remains human?
The smallest solution capable of testing behavior.
Work with real customers and business processes.
Compare the outcome with the baseline.
A playbook to improve, stop, or scale the solution.
An experiment succeeds not when the AI works, but when a customer or financial outcome changes.
05 / RA LAB / DECISION LIBRARY
Start with a challenge. Find a practical guide, a business case and supporting research, then test what applies to your product and market.
06 / OWN LABORATORY · TRAVELTECH
Our own project explores how to help people choose a trip, plan a route and move towards booking.
Owned project · validating demand and business model
Our own project explores how to turn the desire to travel into a practical trip plan. Routes, content, community and AI come together while individual product scenarios are tested separately.
An independent project and an owned laboratory: testing demand and a commission model through travel, product and technology expertise.
07 / EXPERIMENTS
We investigate where AI changes customer behaviour, team performance and business economics. Every experiment begins with a real problem and supports a decision: scale, iterate or stop.
Research agenda: proposed hypotheses, not completed experiments or validated outcomes. An implemented feature does not prove its economic impact.
RetailTech · HONOR
Can context-aware AI recommendations increase paid conversion without compromising margins or recommendation quality?
Customer lifecycle · HONOR
Can AI personalisation grounded in real customer needs increase profitable repeat purchases?
TravelTech · 1 MLN KM
Can AI turn travel inspiration into a verified itinerary that users are willing to adopt?
GRI × GTM · AI economics
Can diagnosing a business constraint help select AI use cases with measurable economic value after all incremental costs?
Human × AI · B2B and services
Can the right division of work between AI and people improve productivity while preserving customer trust and service quality?
Where is your company losing customers, time or profit? Together, we can define a testable hypothesis, meaningful metrics and the right pilot approach.
Propose a business hypothesis →A 21-day test can assess a bounded workflow change. A 90-day business pilot includes baseline measurement, implementation and economic evaluation. Repeat purchases may require 90–180 days or more. These are planning horizons, not promises of results.
Baseline, comparison method, period, sample size, costs, limitations and the decision. Before launch, we define the primary metric, minimum meaningful effect and stopping rules. A null or negative result can still support a useful decision.
08 / AISTART360 · JOIN THE LAB
We bring different kinds of expertise to one challenge. Market knowledge, product, technology and research come together to turn a strong idea into a tested solution.
We start with a challenge, a role and a way to contribute.We find where value is lost
We connect expertise and a testable idea
We measure the effect and make a decision
09 / FOUNDER
Venture Builder · Founder of AIStart360
Marina brings together opportunities, people with different expertise and ideas that can be tested in business. Technology supports that work; the value lies in the outcome for the customer.
More than 15 years of experience across retail, SaaS, FMCG, finance, pharma, logistics and technology projects in Central Asia.
10 / KAZAKHSTAN × UZBEKISTAN
Astana HubTechnology park
IT Park UzbekistanIT ecosystem
MOSTBusiness & capital
AlmaUUniversity
AI & Digital BridgeTechnology forum
CEVFVenture forumWe are developing six locations and gathering interest from companies and local partners. Dates, venues and participation terms will be published once a launch is confirmed.
KazakhstanProposed location
USAProposed location
Proposed location
SwedenProposed location
ChinaProposed location
Proposed location
AI IN CENTRAL ASIA
We work with companies in Kazakhstan and Central Asia to move from AI interest to a measurable operating result—through customer evidence, workflow redesign and controlled field experiments.
We diagnose the customer, data, process and organizational conditions that determine whether an AI use case can create value.
We select one high-value hypothesis, define a baseline and KPI, test the Human × AI workflow and make a Scale / Iterate / Stop decision.
We connect AI to a real customer mission, adoption mechanism, commercial metric and go-to-market plan.
START WITH YOUR QUESTION
Tell us where your business is losing customers, time or money. We will clarify the challenge and identify a next step: an analysis, an experiment or an action your own team can test.
An introductory conversation about one issue. A full audit and implementation plan are a separate engagement. Choose a time and receive confirmation through TidyCal.
