I build companies, organizations, and capabilities that don't exist yet, then run them once we've found product-market fit. Equally comfortable building the function and running it at scale.
acquisition led
$34Macquisition led
person global org
200+person global org
operating budget
$40Moperating budget
run rate, built from zero
$4Mrun rate, built from zero
years operating
26years operating
career brainAI answering from Zach’s record, not Zach
26 years of operating companies, loaded into something you can interrogate. Ask a real question. The answers come from the record, and it will tell you when the record is silent.
or read it the long way
Every chapter, to scale
20052010201520202025
2025 to now
Vursu
2025 to nowCo-Founder & Principal
Turning what the operators know into something the business can query.
AI enablement and knowledge infrastructure for SMB and mid-market operators. The thesis is that most companies don't have an AI problem, they have an undocumented-knowledge problem. Vursu captures what the operators already know and builds the system around it.
Brain Build
A structured knowledge-capture engagement of 10 to 12 working sessions over four weeks, turning undocumented operator knowledge into a system the business can query.
Signal
The subscription layer that keeps captured knowledge current as the business changes.
Serve as embedded fractional AI lead for a growth-stage client at 20 hours per week, building AI processes around the objects the business runs on so leadership can see where work stands, what needs escalation, where mistakes originate, and what puts on-time delivery at risk.
Direct the AI roadmap for a national commercial real estate brokerage under a 10-sprint plan spanning research automation, document generation, and lead scoring and routing into Salesforce. Fixed-fee sprints, each separately scoped and signed.
Designed Brain Build, a structured knowledge-capture engagement of 10 to 12 working sessions over four weeks that converts undocumented operator knowledge into a system the business can query.
Extended engagement work into recurring revenue through Signal, a subscription layer that keeps captured knowledge current as the business changes.
Run a forward-deployed delivery model, placing engineers and contractors inside client environments to build alongside their teams rather than delivering at arm's length.
Lead all product and engineering delivery across the distributed team, with AI-assisted development throughout the stack.
AI
founder
consulting
product
knowledge management
2023 to 2026
Stellar Technology Services
2023 to 2026Co-Founder & Chief Operating Officer
Zero to a $4M run rate and 38 customers on $3.9M raised.
revenue run rate
$4M
capital raised
$3.9M
customers
38
projects delivered
100+
Co-founded and scaled an AI consulting and software engineering firm from inception. Built the entire operating foundation and generated the majority of revenue through founder-led sales.
Co-founded and scaled an AI consulting and software engineering firm from inception to a $4M revenue run rate, raising $3.9M in growth capital.
Generated more than 70% of company revenue through founder-led business development, working directly with executive buyers to shape and close AI consulting engagements.
Grew to 38 customers and delivered 100+ AI and software projects across healthcare, manufacturing, financial services, legal, and staffing.
Established Microsoft Partner and Snowflake Select Partner status; named a Snowflake Startup Challenge semi-finalist.
Built the entire operating foundation, including finance, HR, recruiting, delivery, customer success, resource planning, and vendor management, plus an offshore development capability.
Transitioned out of day-to-day leadership in early 2026 to build a product-focused company. Stellar continues to operate.
AI
founder
COO
sales
consulting
fundraising
2017 to 2023
→Canvas Talent→Jobviteacquired by Jobvite, 2019
2021 to 2023Senior Vice President of Operations, Jobvite
2019 to 2021Vice President of Analytics and Machine Learning, Jobvite
2017 to 2019Vice President of Analytics and Machine Learning, Canvas
200+ people, a $40M budget, and four acquisitions welded into one product.
operating budget
$40M+
global org
200+
incremental revenue
$2M+
companies integrated
4
Six years across Canvas and Jobvite, moving from building the machine learning behind a recruiting platform to running product, engineering, services, and support for the whole enterprise.
Held executive responsibility for product, engineering, professional services, implementation, PMO, support, customer success, and analytics across the enterprise.
Managed a global organization of 200+ employees and a $40M+ operating budget.
Built the attach-rate strategy that integrated Canvas into both Jobvite and Lever, generating more than $2M in incremental revenue within six months of each launch.
Created a senior engineering "Tiger Team" that sharply reduced production defects while improving delivery velocity.
Introduced operational metrics, roadmap governance, and delivery cadences across multiple development organizations, and partnered with executive leadership and private equity stakeholders on operating plans and organizational design.
Led the platform integration of four acquired HR technology companies into one product experience, spanning shared authentication, unified navigation and app switching, a common analytics layer, and API modernization, giving customers a single operational view across products that had been sold, implemented, and supported separately.
Built the first enterprise data platform giving customers one operational view across multiple recruiting products, among the industry's first Snowflake-powered HR analytics platforms.
Led acquisition strategy, diligence, negotiation, and post-merger integration for Predictive Partners.
Built the machine learning and natural language capabilities behind the Canvas recruiting platform, including recommendation systems for interview questions, content, and message wording.
Shipped ML features that reduced recruiter workload and time to fill by generating interview question sets from prior recruiter behavior and optimizing messaging for candidate response rates.
ML
analytics
product
engineering
M&A
private equity
HR tech
Snowflake
2011 to 2017
→Apparatus→Virtusaacquired by Virtusa, 2015
2011 to 2017Vice President of Operations & Head of US Operations
Built a BI practice from nothing to $5M, then sold the company for $34M.
acquisition
$34M
BI practice revenue
$5M+
national team
300+
labor reduction
30–90%
Six years and five titles. Started by conceiving a business intelligence practice that didn't exist, grew it to 25 people and $5M, then took over all technical and delivery operations for a $30M business, and led it through acquisition into a $1B public company.
Progressed from Director of Business Intelligence through Director of Hosting & Managed Services, VP of Operations, and Sr. Director of Operations.
Oversaw all technical and delivery operations, including P&L, staffing, and growth strategy, for a $30M business growing 20% CAGR with 220+ employees.
Conceived and built the Business Intelligence practice, growing it to 25+ people and $5M+ in annual revenue within three years.
Cataloged all work and work types to build the foundation for automated and semi-automated workflows, reducing labor 30 to 90% while improving quality and lowering service prices.
Built a SaaS offering inside a traditional consulting business, creating predictable revenue and non-linear scale.
Led the company through a $34M acquisition by Virtusa, including diligence, negotiation, post-merger integration, and the 90-day transition to public-company SOX compliance. Maintained clean SOC 2, ISO 27001, and Safe Harbor audits.
Designed and stood up a 100-seat global command center in Hyderabad, India in under six months, then ran all US infrastructure operations for a $1B market-cap public company with a national team of 300+.
TechPoint Mira Award, Technology Company of the Year (2015). Ranked No. 7, Indiana Best Places to Work (2015).
BI
operations
M&A
SOX
compliance
P&L
offshore
automation
SaaS
2011
→ExactTargetacquired by Salesforce in 2013, after I left
2011Senior Financial Analyst
Built the infrastructure models that priced the product ahead of the IPO.
A short stint with an outsized artifact, namely the financial models and capacity plans finance used to set price points, and the infrastructure metrics used for SaaS peer comparison in IPO preparation.
Built the infrastructure financial models and capacity plans used by finance to set price points and by the infrastructure team to plan purchases.
Established the infrastructure metrics used for SaaS peer comparison in preparation for the company's IPO.
finance
SaaS
IPO
modeling
2007 to 2010
ChaCha Search, Inc.
2007 to 2010Vice President of Reporting & Yield Management
Two million ads a day, and cost per transaction from $0.54 to under $0.07.
monthly revenue owned
$400K
ads served daily
~2M
cost per transaction
$0.54 → $0.07
Owned every revenue-generating mobile product across every sales channel, and built the systems underneath them, an SMS ad-serving engine and the company's first data warehouse.
Progressed from Sr. Market Analyst through Director of Reporting & Yield Management.
Owned all revenue-generating mobile products across every sales channel, totaling roughly $400K per month.
Designed an SMS ad-serving engine handling approximately two million ads per day, and led the build of the company's first data warehouse.
Cut cost per transaction from $0.54 to under $0.07 as part of the company's path to gross margin profitability.
mobile
ad tech
data warehouse
yield management
unit economics
2005 to 2007
DePuy Orthopaedicsa Johnson & Johnson Company
2005 to 2007Senior Market Research Analyst
Predictive and financial models feeding J&J Investor Relations.
The analytical foundation. Pricing strategy models and market research reporting that went up to Johnson & Johnson Investor Relations.
Built predictive and financial models supporting pricing strategy, and produced market research reporting used by Johnson & Johnson Investor Relations.
I keep the questions people ask the brain, so I can see what is worth adding to the record. Page visits are counted too. No cookies, and nothing that identifies you.
Vursu
