Stack

Investors aren’t impressed by pitch decks. They want traction. That’s why high-growth founders are ditching presentations and shipping AI-native MVPs in under 30 days. The difference? ▪️ They don’t treat AI as an afterthought. ▪️ They build with copilots, predictive logic, and RAG pipelines — from day one. At Stack, we’ve helped 10+ SaaS and fintech ventures: ▪️ Launch investor-ready MVPs in < 4 weeks ▪️ Embed GenAI features from the first commit ▪️ Save 40%+ vs. in-house dev burn ▪️ Scale with confidence — infra, security, and compliance built-in All delivered by our full-stack pods working across the UK & India. ▪️ Skip the prototype despair ▪️ Start showing traction that moves the valuation needle 🤝 Connect with us to see how we can help you ship an AI-native MVP that actually performs. #MVP #ProductEngineering #CustomBuilds #GenAI #Startups #Fintech #SaaSFounders #InvestorReady

Retail GTM Playbooks Are Broken. Not because your team lacks ideas but because your data reacts too late. Most brands still rely on: ▪️ Weekly dashboards ▪️ Static promotions ▪️ Post-hoc customer insights By the time your campaign “learns,” your customers have moved on. What if your GTM engine could think in the moment? At Stack, we’ve helped mid-market retailers: ▪️ Stream real-time behavior data from ecommerce, PoS, CRM ▪️ Layer no-code machine learning for live pricing, stock prediction & churn triggers ▪️ Shift from lagging KPIs to instant interventions With our Smart Data Engineering Suite + AutoMind, clients see results in under 30 days: ▪️ 25% uplift in active conversions ▪️ 40% faster response to trend shifts ▪️ No DevOps bottlenecks. Just AI that works. If your GTM team is tired of running plays with last week’s numbers, maybe it’s time to change the scoreboard. Comment “LIVE” for the cheat sheet on real-time GTM metrics that move margins. #RetailTech #RealtimeGTM #AIinRetail #DemandForecasting

Real-time data is your cheapest consultant. Because firefighting is expensive. Predictive ops isn’t just tech—it’s margin protection. In industrial environments, every delay becomes three:  ▪️ First in detection  ▪️ Then in diagnosis  ▪️ Finally in action But with streaming sensors + AI triggers, your ops team knows before the alarms go off. We’re helping mid-market plants and logistics firms shift from lagging KPIs to live interventions. Result? Downtime falls. Labour gets reallocated. Capex gets smarter. Predictive ops doesn't mean buying a data lake. It means connecting what you already have and asking better questions, faster. Comment “OPS” for the KPI cheat list – the ones your board actually cares about. #PredictiveOps #IndustrialAI #RealTimeData #AIForIndustry

Data silos aren’t just a tech issue — they’re a speed tax. A leading education provider came to us with 4 disconnected systems and 2.5 million records. Fragmented views. Manual reconciliations. And operations that moved at half the pace.   Here’s what we did👇 ▪️ Unified 2.5M+ records across systems ▪️ Delivered enterprise-wide master data in under 12 weeks ▪️ Enabled 25% faster downstream operations   The secret? Stack’s 3-step Data Mesh approach: ▪️ Decentralise responsibly — Source-aligned domains, not chaos ▪️ Productise data — Governance + discovery baked in ▪️ Enable real-time — Low-latency pipelines, audit-ready lineage This isn’t theory. It’s working. We’re now applying the same pattern across healthcare, retail, and BFSI.   Thinking of cleaning up your data estate? We offer a discovery sprint to assess readiness and design your mesh map. DM or Comment ‘MESH DIAGNOSTIC’ to book a slot. #DataEngineering #AIReadyData #DigitalOps #DataMesh #EnterpriseAI

AI pilots don’t need 6 months to get moving. We helped an industrial ops team go from backlog chaos to smart triage— ▪️ 26% faster resolution ▪️100% audit-compliant ▪️And the pilot signed off in 48 hours. The trick? ▪️ Target ops pain, not AI hype ▪️ Use modular data infrastructure ▪️ Present a pilot business case, not a tech deck We’ve distilled this into a short playbook. Read the full breakdown + book your own blueprint session. #IndustrialAI #SmartOps #DataEngineering #AIpilot #COOplaybook #ManufacturingTech #DigitalTransformation 

Supply chains don’t break overnight; they bleed slowly through missed KPIs and manual blind spots. Here’s a quick look at the metrics that help you cut costs and regain control. Want us to audit your current setup? Comment “AUDIT” and we’ll map your gaps. #SupplyChainAnalytics #RetailTech #AIforOps 

Speed doesn’t kill—context switching does.  That’s where your burn goes. Hidden. Bleeding out.  Not in delivery velocity, but in decision latency.  Every time your team pivots from product to infra, or from features to fine-tuning models, you pay the context tax. Low-code ML isn’t about skipping engineering. It’s about buying back focus.  So your best minds aren’t stuck wiring glue code or interpreting notebooks.  In scale-up mode, the real win is not faster models—  It’s fewer meetings, fewer handovers, cleaner loops.  We're helping SaaS teams stay product-focused and AI-native.  Want to know how many dev-hours you’re burning in context churn?  👇  Comment “CONTEXT” for the calc sheet. #ProductEngineering #EnterpriseAI #NoCodeML #TechDebt #DeveloperProductivity

Marketing campaigns often miss the mark—not because of creativity, but because of poor segmentation. With AutoMind, we helped a fast-scaling brand uncover four high-impact customer clusters—no code, full transparency. The result? Smarter targeting, better ROI, and faster insight-to-action. #CustomerSegmentation #RetailAI #NoCodeML #MarketingAnalytics

Cloud infra spend creeping up quietly? For scale-up SaaS teams, it usually starts after Series A: Shipping velocity increases, environments multiply, and suddenly ...... You're paying for infra you don’t even use. We see it all the time. Costs growing 30–50% faster than revenue, with no one tracking unit economics per feature or API. That’s why we built this short playbook written from our direct experience: “Cut 15% Cloud Infra Cost in 90 Days : SaaS Edition.” Inside: ▪️ The 3 silent infra leaks in modern SaaS stacks ▪️ A benchmark ratio: cost per dollar of ARR ▪️ A 90-day plan you can run without slowing your product roadmap It’s what we’ve used with teams scaling on GCP, Supabase, and Vercel >> with clean results and CFO-ready optics. DM us or comment “CLOUD-15” and we’ll send you the playbook. #CloudEngineering #SaaSOps #InfraOptimisation #EnterpriseAI  

Most ML pilots stall before they start, buried in tooling, talent gaps, or compliance complexity. With AutoMind, you skip the noise and go straight to value. ▪️ Drag-and-drop model builder ▪️ Built-in explainability (SHAP) ▪️ Real-world use cases in Finance, CPG, and Retail   One platform. No black boxes. Book a demo and see how fast your team can launch ML that actually ships.   #EnterpriseAI #MLOps #AutoMind #AIinProduction #DataDrivenDecisions