Knows When to Act.
Knows When to Ask.
62% of AI pilots never reach production. Multikor solves the #1 barrier — operationalization. Our three-layer architecture — Autonomous Data Fabric, Delta Intelligence Engine, and Self-Healing CI/CD — delivers production-grade back-office automation for SMBs at 20% of traditional time and 10% of traditional cost. Zero AI engineers required. The platform compounds intelligence with every deployment.
The Opportunity: The Operationalization Gap
62% of organizations are stuck in AI pilots that never reach production. Only 23% are scaling agentic AI. With just 5.4% AI adoption, 33M US companies lack AI implementation capability. The gap isn't technology — it's operationalization. SMBs face this even more acutely: no AI teams, no 12-month implementation budgets, no margin for failed experiments. Multikor delivers production-grade AI that actually ships.
Market Opportunity Breakdown
The Opportunity: McKinsey's 2025 AI Report shows 62% of organizations are stuck in pilots, and only 23% are scaling agentic AI. With only 5.4% AI adoption among SMBs and 33M US companies lacking AI implementation capability, the gap is enormous. SMBs don't have dedicated AI budgets or AI engineers—they need production-ready automation, not AI software to build themselves. Multikor's three-layer architecture (Autonomous Data Fabric, Delta Intelligence Engine, Self-Healing CI/CD) delivers production-grade orchestration at 20% of the time and 10% of the cost, starting with SMB and growing into mid-market and enterprise segments.
The Solution: Three-Layer Agentic Architecture
Multikor's production-grade platform orchestrates autonomous back-office automation through a three-layer architecture: the Autonomous Data Fabric ingests and normalizes enterprise data, the Delta Intelligence Engine detects changes and routes decisions, and the Self-Healing CI/CD pipeline deploys and maintains workflows with 95% auto-remediation. Our 4-tier SLM hierarchy handles 70% of requests at near-zero cost, with confidence-based escalation that knows when to act and when to ask.
Platform at a Glance
Why Multikor Wins: Anti-Commoditization by Design
Domain-Specific SLMs
Purpose-built Small Language Models trained on real workflow data per discipline. 70% of requests handled at ~$0 cost—can't be replicated by generic LLM wrappers.
Delta Intelligence Engine
Change-detection layer that identifies what's different, what matters, and what to do next. Confidence-based routing ensures agents act autonomously when certain and escalate when not.
Pilot-Driven Expansion
Break through the 62% pilot trap. Multikor's MVP is live — we're negotiating our first customer pilot with Apexon (5,500 engineers, Goldman Sachs-backed), then scale proven services to similar companies.
Enterprise EBIT Impact
Transformative AI drives measurable business outcomes: revenue growth, innovation enablement, and operational efficiency—not just cost savings.
Self-Healing Architecture
95% self-healing rate with 24 feedback loops, circuit breakers, auto-rollback, and AI-driven prompt enhancement. The platform gets smarter with every deployment.
Platform Live & Operational
Multikor MVP deployed and operational — production-grade infrastructure ready
✓ Multikor MVP Complete
Production-grade platform deployed and operational
✓ Apexon Pilot in Negotiation
First customer pilot being negotiated with Apexon (5,500 engineers)
✓ Platform Infrastructure
AWS-native with Neptune Analytics + SLM architecture
✓ Initial Partner Validation
5,500 engineers, Goldman Sachs-backed partner confirmed approach
The Market: $500B+ TAM
Two-phase market strategy with massive opportunity
SMB-First + Growth Ladder
2026-2028BPO Channel (Concurrent)
2026-2028Market Breakdown by Back-Office Discipline
Explore the Full Story
Detailed investor information across dedicated sections
Product & Competitive
SLM architecture, methodology guardrails, competitive differentiation, and technology highlights
Business Model
Autonomous automation subscription, unit economics, and path to high gross margins
Financials
Revenue projections, traction milestones, investment terms, and use of funds
GTM Strategy
SMB-first beachhead, BPO concurrent channel, pilot-driven expansion strategy
Pricing Details
AWS infrastructure costs, COGS analysis, and investor-grade margin calculations
Team & Exit
World-class leadership, Series A roadmap, exit scenarios, and investment highlights