I am Kabiru Awulu. In 14 years I went from supporting 9,000 base stations on MTN Nigeria's network to heading service delivery and IT at a YC-backed health tech company, to serving as a Chief AI Transformation Officer. I lead technology organisations, and I personally build the agents, automation and products they run on. Most people do one or the other. I do both, and Antler picked me as one of 32 builders from nearly 7,000 applicants partly for that reason.
Real systems, in production, doing jobs people used to do by hand.
Sales reps at a YC-backed insurance technology company were spending hours a week building lead lists by hand, checking them against the CRM, and writing outreach one message at a time.
I built an eight step pipeline that reads the ideal customer profile from a spreadsheet, searches Apollo at four times the target volume so the good leads survive filtering, deduplicates against HubSpot in parallel, pulls market intelligence on each company, and has GPT-4 write personalised LinkedIn, email and WhatsApp messages in the company's own outbound voice. A Gmail layer sequences the sends, tracks replies, and hands the thread to a human the moment a prospect responds.
Manual prospecting hours per rep went to near zero. Campaigns start with one click, and cost tracking is built into every run.
Hiring was slow and inconsistent. Resumes piled up unread and every interviewer scored differently.
I built two connected products. A recruiter agent inside the HR platform screens every incoming resume and runs the pipeline from application to hire recommendation. An interview tool takes a pasted job description, generates a tailored assessment, lets candidates answer by text or voice, and produces a three tier evaluation: resume scorecard, assessment scorecard, and final recommendation. When the job description changes, evaluations re-run so decisions stay current.
Every CV gets parsed and scored. Interviewers work from the same rubric, and hiring decisions come with an audit trail.
Leadership updates lived in thousands of Slack messages and meeting recordings nobody had time to read.
I built a reporting suite that drew on more than 10,000 Slack messages and 2,850 meeting transcripts to produce a daily organisation report, a morning brief, blocker detection and execution tracking, all delivered where leadership already works. In parallel I rebuilt how the company's AI workloads ran, adding prompt caching, semantic caching, model routing and request batching.
Leadership got one daily picture of the company instead of forty threads, and AI operating costs dropped by about 70 percent.
Most AI rollouts fail the same way: a clever tool ships, three people use it, and six months later it is dead. The technology was never the hard part. Adoption is.
At the same insurtech I deployed 7 AI agents, one personalised for each of seven teams, delivered inside Slack where each team already worked instead of behind yet another login. Around them I built the adoption machine: a 30 day enablement plan that took every team from first exposure to daily use, hands-on workshops and training, an AI community of practice, quarterly competency assessments to measure who was actually gaining skill, and governance standards so people knew what safe use looked like.
Company-wide adoption across product, engineering, sales, customer success, HR and operations. The ~40 percent software cost reduction only happened because teams genuinely switched. Tools do not change companies. Enablement does.
Customer success found out accounts were unhealthy at renewal time, when it was too late to act.
I built a monitor that pulls weekly operations data, computes deterministic risk scores per account, and routes alerts to Slack and email with cooldowns so nobody drowns in noise. Every alert and follow up is persisted, so account history is there when someone picks up the phone.
Risk surfaces weeks earlier, with the trend data to back up the conversation.
Crystal Specialist Hospital in Lagos had unreliable clinical systems and no clear picture of what hardware and infrastructure they actually had.
I ran a 90 day stabilisation: restored the clinical systems, audited the infrastructure, and defined the technology roadmap. To run the engagement I built a field workspace app that works fully offline on a phone, captures findings by voice and camera in the server room, and syncs to a desktop app for structuring and reporting.
Clinical systems back in service, a documented estate, and a roadmap the hospital's leadership is executing against.
Each of these is a complete build: strategy, brand, code, database, deployment. This is the range I bring to a client engagement. Click any product for the full story.
Most consultants bring one of these. The value is in having all three at the same table.
Independent AI and technology consulting: AI transformation, intelligent automation, product delivery and information security for client organisations. Engagements so far:
Crystal Specialist Hospital, Lagos. A 90 day technology and operations stabilisation. Restored clinical systems, audited infrastructure, and defined the hospital's technology roadmap.
Zinolynn Technologies. Led delivery of e-commerce payment gateway plugins for two banking clients, covering product delivery, project management and information security.
Partnered with the CEO on the company's AI-first operating model. Built and deployed 7 AI agents, one personalised for each of seven teams and delivered on Slack, plus 20 plus workflow automations and internal AI products across HR, sales, customer success, product and operations, cutting software costs by about 40 percent and AI operating costs by about 70 percent. Led a team of 3 AI engineers, and drove company-wide adoption through a 30 day enablement plan, workshops, an AI community of practice, quarterly competency assessments and governance standards.
Selected as 1 of 32 builders from nearly 7,000 applicants, roughly the top half of one percent, into one of the world's leading founder development programs. Explored venture creation through customer discovery, rapid product validation and business development, focused on enterprise AI adoption, workflow transformation, AI governance and operational tooling.
Head of IT and Service Delivery, previously Senior Tech Support Manager. Led IT, customer and technical support, and the project management office: a 22 person team of managers, trainers, engineers and project managers, plus 20 plus vendors and a $300K budget. Platforms under my teams served 300 plus healthcare organisations, more than 10,000 users and over a million patient records. Cut major deployment timelines by around 60 percent, launched a certification program that scaled trained deployment professionals across regions, and served as Data Protection Officer for NDPR and ISO 27001 compliance.
Eleven years, engineer to global consultant. Supported 9,000 plus base stations carrying around 30 million MTN Nigeria subscribers, led a 20 plus person service desk across Nigeria and India, ran change and problem management for the national packet core, then went global: program lead for service operations and automation across five managed services accounts on four continents. Product owner for the automation tools that delivered over $2M in savings, and named MVP of the global Service Delivery Evolution Program.
BSc Computer Science, Babcock University. Executive education at Yale School of Management. ITIL, PRINCE2, ISO 27001 Lead Implementer, Lean Six Sigma.