Founder-led AI consulting for teams that need systems in production.
Elephant Stripes helps organisations turn AI opportunities into working software, reliable workflows, and measurable adoption. Engagements are led by Tat Banerjee, an AI solutions and delivery consultant with engineering, finance, and enterprise rollout experience, backed by a team that builds production systems.
Senior judgement before the team starts building.
Tat Banerjee leads AI solution design and delivery at Elephant Stripes. His background spans systems engineering, software delivery, applied finance, regulated financial markets, startup operations, and production AI product development.
That mix matters because AI projects rarely fail because the model is not clever enough. They fail because the use case is vague, stakeholders are misaligned, workflows are misunderstood, governance is bolted on too late, or adoption is not measured.
Engineering + IT
Systems Engineering and Information Technology foundations from ANU.
Applied finance
Master of Applied Finance from Macquarie University.
Regulated delivery
Seven years across financial services and regulated markets at State Street.
Production AI
Founder/operator behind VideoTranslatorAI and principal AI consultant through Elephant Stripes.
AI workflows
Delivery across GenAI, AI agents, workflow automation, integrations, and governance.
Enterprise rollout
Stakeholder work across business, technology, legal, compliance, vendors, and client teams.
Direct access to the lead, backed by builders.
Clients work directly with Tat on problem framing, stakeholder alignment, solution design, and delivery priorities. Behind that engagement is the Elephant Stripes team: builders, operators, and specialists who turn the agreed direction into software, integrations, automation, analytics, and production support.
- Tat leads discovery, solution framing, senior stakeholder communication, and accountability.
- The team supports AI workflows, integrations, analytics, infrastructure, and content systems.
- Engagements stay practical: define the outcome, build the smallest useful system, measure adoption, and improve from usage.
Tested in public-sector contexts, not just private demos.
The team behind Elephant Stripes has taken AI products through NSW Government grant programs, emergency-management collaborations, SBS World News coverage, AFAC recognition, and healthcare-accessibility Proof of Concept work.
Government programs
JobsForNSW MVP Grant, NSW Natural Hazards Technology Program, and NSW SBIR healthcare work.
View evidence ↗Emergency and healthcare use cases
Multilingual hazard alerts, CALD healthcare access, and complex conversations in high-stakes settings.
View evidence ↗Public credibility
AFAC23, AFAC24 ministerial recognition, SBS World News, Firetech Connect, and Asia Pacific Fire Magazine.
View evidence ↗Shipped products shape the consulting.
Elephant Stripes work is grounded in production AI platforms and private client systems, not slideware. The same delivery habits carry into consulting engagements.
VideoTranslatorAI
A production Generative AI SaaS platform for multilingual communication and localisation workflows.
- NSW Government grant and program validation
- Emergency-management and healthcare-accessibility use cases
- SBS World News, AFAC, and Asia Pacific Fire Magazine evidence
JobsLobster
An AI agent-powered job matching and candidate-positioning platform.
- NLP and automated candidate workflows
- Candidate-role discovery at scale
- AI agents applied to practical user workflows
SpeechLobster
An LLM and audio-ML speech application for real-world operational use cases.
- Voice and audio AI capability
- Applied language-learning workflows
- Operational product design beyond experiments
Bespoke client systems
Private AI applications, integrations, automation, and content systems for clients.
- Requirements discovery and stakeholder alignment
- Governance and adoption considerations
- ROI and usage measurement built into delivery
Practical steps from problem to production.
Diagnose the workflow
Map the process, stakeholders, systems, risk points, and success metrics.
Shape the AI use case
Decide where AI should help, where it should not, and what needs human review.
Build the first useful system
Prototype quickly, integrate with real tools, and avoid theatre demos.
Govern and measure
Define KPIs, adoption signals, ROI measures, and responsible-use boundaries.
Improve from usage
Iterate based on real users, real data, and real operational friction.
Bring a real AI problem.
If your organisation has an AI opportunity, a workflow bottleneck, or a half-built idea that needs senior delivery judgement, start with a conversation. We will help you decide what is worth building, what is not, and what it would take to ship responsibly.