OneXus Global

Live working sessions · Executive briefings · Custom cadence

Upskill your teams on practical AI
with enterprise facilitators

Workshops, multi-week bootcamps, and quarter-long academies for engineering, data, and product orgs. Facilitators active at Oracle, Microsoft, and Tech Mahindra help you align pilots to governance, stack, and ROI narratives your executives already use.

Experts from

Tech Mahindra

Microsoft

Oracle

✓
Discovery workshop to map stakeholders, data boundaries, and success metrics before day one
✓
Hands-on labs on LLMs, RAG, MLOps, and cloud AI patterns your teams can reuse internally
✓
Capstones and demo days designed for engineering directors and business sponsors
✓
Optional train-the-trainer kits and playbooks so learning continues after the engagement
✓
NDA-friendly delivery and recordings governed by your collaboration policies

⭐ Practitioner-led delivery

👥 Cohorts from 15–500+

🏢 Fortune 500 experience

🕐 Virtual, hybrid, or on-site

OneXus Global

Corporate discovery & proposal

Workshops
to academies

Fixed-fee pilots, milestone billing, or retainer — scoped after a short discovery call

Typical reply within 1 business day

📋 FormatWorkshop · bootcamp · or multi-month academy

🏢 AudienceEngineering, data, product, L&D, IT

📍 DeliveryYour VPC / tenant patterns where required

🎓 OutcomesRubrics, capstones, exec readouts

🌐 RegionsAPAC, US, EU-friendly time blocks

🔒 Information held confidential · No obligation · Enterprise references on request

🎉

Request received

Thank you — our enterprise team will respond with next steps and an optional calendar link.

We look forward to learning about your teams. 🚀

Facilitators with enterprise delivery experience

Practitioners who have shipped AI at global scale

⬡ Tech Mahindra

Gowtham

AI Solutions Architect · Tech Mahindra

8 yrs experience

8 years deploying enterprise AI for Fortune 500 clients across banking, telecom & manufacturing. Expert at translating real business problems into production ML systems that scale.

Enterprise AINLPAutoMLLangChainAI Strategy

⬡ Microsoft

Ankur Mishra

Senior AI Engineer · Microsoft Azure

15 yrs experience

15 years at Microsoft building Azure Cognitive Services and Copilot integrations. Trained 500+ engineers on practical LLM use — passionate about making AI accessible to non-CS professionals.

Azure AILLMs / GPT-4Copilot DevPyTorch

⬡ Oracle

Parikshit Shukla

Principal Data Engineer · Oracle India

12 yrs experience

12 years building production AI & data pipelines at Oracle. Led ML integrations for Oracle Analytics Cloud serving 3M+ enterprise users. Known for making complex AI concepts click for beginners.

PythonOracle AnalyticsMLOpsSQL + AI

Modular tracks for engineering, data & product

A curriculum that maps to your stack & KPIs

Module 01

Executive AI literacy & governance

ROI framing, risk registers, and responsible-AI checkpoints
How to evaluate vendors, pilots, and internal build-vs-buy
Aligning legal, security, and product on a common vocabulary

💼 Board-ready briefing template

Module 02

Data platforms for ML at scale

Feature stores, lineage, and access patterns your Infosec team will accept
Batch vs real-time inference — cost and latency trade-offs
Connecting warehouses, lakes, and SaaS to model pipelines

📊 Reference architecture walkthrough

Module 03

MLOps & production readiness

CI/CD for models, environments, and rollback strategies
Monitoring drift, performance, and fairness in production
Audit trails and documentation hiring managers expect

⚙️ Live pipeline review

Module 04

LLMs & RAG on private knowledge

Chunking, embeddings, and retrieval tuned to your documents
Grounding, citations, and reducing hallucinations in the enterprise
Patterns for support, sales enablement, and internal search

🧠 Secure RAG design lab

Module 05

Agents & workflow automation

Human-in-the-loop approvals and tool boundaries
Orchestration with patterns used by platform teams
When to automate end-to-end vs assistive copilots

🚀 Ops automation scenario

Module 06

GenAI for product & UX

Prompt systems, eval suites, and release discipline
UX patterns for trust, disclosure, and failure states
Cost/latency budgets for customer-facing features

🎨 Product critique working session

Module 07

Cloud AI & your tenancy

Azure AI, Oracle AI services, and API governance
Identity, keys, and network boundaries for regulated workloads
Blueprints teams reuse across business units

☁️ Landing zone alignment

Module 08

Fine-tuning, adapters & cost control

When RAG is enough — and when to fine-tune
Parameter-efficient methods and evaluation gates
Token economics and caching strategies

📈 TCO sensitivity model

Module 09

Capstones tied to business outcomes

4–8 week pilots with milestones your sponsors can score
Demo days for leadership and internal certification options
Handover kits for your internal champions

🏆 Executive demo playbook

Module 10

Sustainability & train-the-trainer

Playbooks, office hours, and internal office-of-best-practices
Upskilling internal facilitators and guild models
Roadmap for the next two quarters of capability building

📚 Knowledge transfer pack

Who we partner with

Built for teams that need measurable AI capability

🔧

Engineering & platform

Standardize how squads ship ML and LLM features with reviews, tooling, and deployment patterns that scale.

📈

Data & analytics

Move from one-off notebooks to governed pipelines, feature practices, and observability your stakeholders trust.

🎨

Product & digital

Give PMs and designers a practical lens on GenAI UX, evals, and shipping responsibly in live products.

🎓

L&D and people leaders

Run cohort-based academies with rubrics, manager syncs, and proof-of-skill instead of slide-only training.

👨‍💼

IT, security & compliance

Clarify data flows, model risk, and vendor patterns so pilots pass review without stalling innovation.

🏢

CXOs & transformation

Get concise narratives on ROI, portfolio sequencing, and what “good” looks like at 90-day horizons.

⚠️

We may not be the right fit if… You need a one-hour generic awareness webinar with no hands-on work, or you cannot sponsor a business owner for scoping and pilot success metrics. We focus on cohorts that ship or decide with evidence.

Outcomes your sponsors can recognize

What teams ship or decide

📁

Governed pilot charter

A one-page scope your security, legal, and product leads can sign off on before work begins.

🤖

Baseline ML & eval harness

Reusable notebooks and metrics templates so teams compare models the same way across squads.

📊

RAG on internal knowledge

Reference design for retrieval, access control, and citation patterns on your own documents.

⚙️

MLOps / LLMOps checklist

CI/CD hooks, monitoring, and rollback steps mapped to tools you already pay for.

🧠

Executive readout deck

Slides and talking points for sponsors: ROI, risk, and next funding gate — not just tech deep dives.

☁️

Handover playbook

Runbooks and office-hour structure so internal champions sustain momentum after facilitators step back.

Fit check

Sound familiar for your organization?

✓

Leaders ask for an "AI strategy" but teams lack a shared vocabulary between business, security, and engineering.

✓

You have strong ICs, but pilots stall because nobody owns data access, evals, and production gates end-to-end.

✓

Generic vendor training doesn't map to your stack, compliance rules, or internal platform choices.

✓

You need facilitators who have shipped models and LLM features in regulated, high-scale environments — not slide-only coaches.

✓

You want capstones and rubrics that managers and VPs can score, not attendance certificates alone.

✓

You're ready to sponsor a focused discovery and a pilot cohort with clear success metrics this quarter.

🎉 Strong fit for a corporate academy

You selected patterns we see in teams ready for facilitated cohorts and executive alignment. Share your context and we'll propose a delivery model.

What program sponsors say

Outcomes from enterprise cohorts

★★★★★

We finally got security, data, and product in the same room with shared diagrams. The capstone demo became our template for approving the next three GenAI pilots.

👨

Priya N.

VP Engineering · B2B SaaS · Faster pilot approvals

★★★★★

Our L&D team needed something heavier than awareness webinars. Cohort NPS went up and managers reported clearer expectations after the rubric-based reviews.

👩

Daniel K.

Head of L&D · Financial services · Measurable skill lift

★★★★★

Gowtham's enterprise framing helped our data platform team standardize how squads request GPU budgets and document model risk. It felt like consulting with homework that stuck.

👨

Meera S.

Director, Data Platform · Telecom · Shared governance model

★★★★★

We appreciated that facilitators still ship in production contexts. The examples weren't academic — they were the same trade-offs we debate in architecture reviews.

👩

James L.

Chief Digital Officer · Manufacturing · Credible vendor conversations

★★★★★

We ran a hybrid cohort across three regions. Recordings plus office hours meant teams in smaller sites weren't left behind — huge for adoption.

👨

Elena R.

IT Strategy · Global logistics · Consistent delivery globally

📷

Your logo / quote
after your first cohort

Our Philosophy

Build durable AI capability not one-off workshops

Industry Use-Cases First

We anchor every module on decisions your executives and tech leads actually make — funding, risk, and sequencing — not abstract definitions.

Live Coding Every Session

Practitioners facilitate live builds and reviews. Leaders get executive summaries; engineers get repos and checklists they can reuse.

Enterprise-Grade Toolstack

We meet you on Python, Azure AI, Oracle Analytics, HuggingFace, LangChain, and the internal services you already operate.

Portfolio-Ready Output

Teams leave with pilot artifacts, playbooks, and sponsor-ready readouts — assets that outlast any single training week.

Procurement, delivery & outcomes

Common questions from L&D and engineering leads

Can you align content to our internal stack and compliance rules?▼

Yes. We start with a discovery workshop, review your approved toolchains and data boundaries, then tailor labs and capstones so teams practice on patterns they can actually deploy.

Do you deliver virtually, on-site, or hybrid?▼

All of the above. Most programs blend live facilitated sessions with async projects and office hours. We can run intensive on-sites for leadership or distributed cohorts across regions.

What cohort sizes work best?▼

Hands-on tracks work well from 15–40 practitioners per cohort with breakout coaching. For executives we often run smaller forums (8–15) with different pacing and case studies.

How do you measure impact for our stakeholders?▼

We agree on skill rubrics, milestone demos, and optionally manager sign-offs. Many clients pair our capstones with internal hackathons or production pilot gates.

Will you sign an NDA and work with our Infosec review?▼

Standard for enterprise engagements. We use your collaboration tools where required and can keep exercises on synthetic or approved datasets until clearance is granted.

What happens after the first academy?▼

We typically leave playbooks, office-hour options, and a roadmap for advanced tracks (MLOps depth, agentic systems, domain-specific LLMs). No forced lock-in — many teams continue with quarterly deep dives.

Upskill your teams on practical AIwith enterprise facilitators

Scope your next AI academy

Upskill your teams on practical AI
with enterprise facilitators