Veritek
Veritek — Fractional CTO / Fractional CEO / AI Strategy & Architecture Advisor

Building Solutions That Do Not Yet Exist.

12+ years as founder, owner, and technical director building AI and data-driven platforms from the ground up — for banks, multinational corporations, and election campaigns. Not an interim manager who stabilizes someone else's system. My specialty is 0→1.

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Automated regulatory reporting

Regulatory & Compliance

Transfer pricing and IAS 19 studies, generated by an AI system and checked by people — currently covering Serbia and the EU.

01

You send us the underlying data and documentation through a secure channel.

02

Our AI system drafts the study, structured to the applicable IFRS/OECD/transfer pricing framework.

03

A human reviewer checks the draft for accuracy before it's finalized and delivered in your format.

Reports delivered in hours, not weeks.
Automated search across both closed and open databases.
Delivered as Word or PDF — editable further on request.
For advisors

Studies for clients, accountants & audit firms

  • We work directly with clients, accountants, and audit firms to produce transfer pricing studies.
  • Our AI system automates the entire production process; every study is reviewed by our team before delivery.
  • Full GDPR and security procedures in place, covering data privacy and retention end to end.
  • Send us your data, and we return a completed report — reviewed by our team before it reaches you.
  • Priced at 50% of our standard full-service rate for companies — since you already hold the client relationship and underlying data.
For enterprises

Managed reporting & self-service (SaaS)

  • We set up the service for internal use, so your own employees generate and review reports themselves, on demand.
  • Reports are personalized to match each client's own template and way of working.
  • Full GDPR and security procedures in place, covering data privacy and retention end to end.
  • Send us your data, and we return a completed report — reviewed by our team before it reaches you.
  • Priced fixed per report based on complexity, across two tiers — pricing scales with report volume, with a minimum number of reports guaranteed annually by the client.
  • Fully compliant with the requirements of tax authorities and regulators.

Also available for IAS 19: the same two models — advisor-delivered studies or managed/SaaS reporting — apply to IAS 19 (employee benefits) reporting.

Talk to us about your reporting needs
What we offer

Four ways to work together

Build

AI/data platforms from scratch

When a company has the idea and the data, but not the team or architecture to turn it into a product.

Advise

AI Strategy & Architecture

Designing and validating architecture before a company invests in the wrong solution.

Lead

Fractional CTO / Fractional CEO / Head of AI

Ongoing technical leadership, 1–3 days per week, for companies that don't yet need a full-time executive.

Assess

Investor Due Diligence

Technical assessment of AI/data startups prior to investment.

  • 12+Years building AI & data platforms
  • ~40People led on a single engagement
  • 7Patents & software copyrights
  • 0→1What I actually specialize in
Founder — Not a firefighter

I'm not brought in to stabilize a system someone else built. I'm brought in when the tool a company needs doesn't exist yet — or when the vendors on the market, including established names like IBM, can't solve the actual problem.

Across banking, consumer goods, capital markets, and political analytics, the pattern has repeated: an organization has a real question it cannot answer with the tools it already owns. I've built the architecture, led the team, and shipped the product that answered it — from the first line of code to a signed contract.

— Vladimir Petrović, Founder

Bright Minds

30+ great people work, create, and innovate every day. Our talented people are our greatest asset. With their spirit, dedication, and engagement, we create exceptional technologies with innovative applications we use every day to create insights, strategies, and sustainable value.

Selected engagements

Case files

Case file — Capital markets

Predictive AI for cryptocurrency markets (BTC)

FILE / 02
  • Designed a system correlating social media sentiment with Bitcoin price, achieving predictive signal on a ~72-hour horizon.
  • Processed 113 TB of blockchain data, 30 million conversations, 1.5 million unique authors.
  • Classified BTC wallets into 7 size groups and validated findings through cross-referencing and reverse validation.

Key finding: small holders — not large players — correlate most strongly with price movements.

Chart correlating BTC price with social sentiment reach
Sentiment reach vs. BTC price, annotated hike/drop signals
Chart of wallet transaction volume by size group
Wallet transaction volume by size group vs. BTC close
Case file — Consumer goods

P&G (Pampers) — uncovering the real cause of a sales decline

FILE / 03
  • Word Cloud analysis identified an unexpectedly high frequency of the word "Amazon" in public conversation.
  • Revealed that the decline in in-store sales was actually a shift to online purchasing via discounted Amazon listings — a root cause the P&G team could not identify on its own.

455,327 posts analyzed · 1.64M reach · 1-week research window.

Word cloud dominated by the word Pampers, Amazon, and baby-related terms
Word Cloud output — "Amazon" surfaces as a dominant, unplanned term
Case file — Consumer goods · Crisis response

Gillette — reading the real reaction to "We Believe"

FILE / 04
  • Traditional media coverage of the "We Believe" campaign quoted mostly negative reactions.
  • Social listening told a different story: broad public sentiment was considerably more positive than the press narrative suggested.
  • Reach of 43.1M, engagement of 1.25M, and 7,138 mentions tracked and segmented by sentiment across the full campaign window.

The gap between media narrative and public sentiment was the actual finding.

Gillette We Believe campaign infographic with reach, engagement, sentiment and top influencers
Campaign infographic — reach, sentiment trend and top influencers
Case file — Brand & reputational risk

Cadbury's / Lindt — a risk nobody was looking for

FILE / 05
  • Comparative sentiment and marketing-performance analysis ahead of Easter; Cadbury's identified as the leader in both categories.
  • A second, unplanned finding surfaced through word-trend analysis: significant negative sentiment linked to Lindt's palm oil sourcing and habitat destruction.

20.9M reach across 745 posts — the reputational signal that mattered wasn't the one anyone was looking for.

Case file — Political & election analytics · U.S. & regional

Election analytics platform — sentiment, influence, and geography at scale

FILE / 06
  • Led a team of ~40 people building and delivering a real-time analytics platform for election campaigns — sentiment, media networks, donations, and state-level geography.
  • Platform used across multiple U.S. election cycles (including the 2016 and 2019/2020 presidential races) and regional elections.
  • Accuracy example: a comparative analysis of three candidates for a 2018 Florida State House District 72 race correctly predicted the final placement of all three parties with 100% accuracy, based on just 3 days of research.

The system combined sentiment analysis, media-network mapping, and state-level geo-analytics in real time.

Deep sentiment coordinate chart for the Florida State House District 72 race
Deep Sentiment tracking — Florida State House District 72, 2018
Treemap of campaign contributions by state and occupation
FEC contribution data — by state, occupation, and donation volume
Network graph of top media authors and their reach by platform
Media network mapping — top authors, reach, and platform
Under the hood

Inside a platform built for this kind of work

A representative view of the analytics platform architecture I've built and led — dashboards, sentiment tracking, influence networks, and geographic distribution, all in real time.

Platform dashboard overview with mentions, reach and top authors
Dashboard — mentions, reach, engagement at a glance
Sentiment trend line chart over time
Sentiment tracking over time
Network graph of influencers colored by sentiment
Influencer network, colored by sentiment
World map showing geographic distribution of mentions
Geographic distribution of public conversation
Deep sentiment coordinate chart and emotion radar
Deep Sentiment & Emotion Radar
Methodology

The modeling behind the sentiment layer

The emotional classification underlying these platforms is grounded in established psychological models — not a black box.

Circumplex model of affect diagram
Circumplex model of affect — valence & arousal
Diagram of core AI categories: machine learning, NLP
Core architecture — ML & NLP building blocks
Intellectual property

Patents & copyrights

YearTypeTitle
2016Software copyrightMathematical intelligence algorithm for data analysis
2020Software copyrightArtificial intelligence for big data analysis
2020Software copyrightArtificial intelligence for use in finance
2025Software copyrightAI software for logistics support
2025Software copyrightAI algorithm for analyzing data from multiple sources
2025Software copyrightAI algorithm for generating international financial reports
Engagement

Let's talk about what you're trying to build.

Open to remote collaboration with companies in the EU and U.S. Available for an introductory call to assess whether and how I can help with a specific challenge — architecture, strategy, or technical leadership.

Email
office@veritek-global.com