Team: World-Class Technical & Business Leadership

Proven track record in enterprise software and AI/ML

Suresh Nelakantam

Suresh Nelakantam

CEO & Co-Founder
suresh@multikor.ai

Seasoned technology executive with 20+ years building and scaling enterprise platforms with deep expertise in AI-first transformation.

Key Achievements:

  • SVP of Engineering, RxSense: Led AI-driven modernization of platform processing 6B+ transactions annually
  • • Integrated RAG-based knowledge systems and AI agents across SDLC
  • • Translated AI innovation into measurable outcomes: scale, reliability, revenue growth

Leadership Focus:

Embedding AI into products, platforms, and operating models to drive faster execution, higher margins, and durable competitive advantage

Leigh Turner

Leigh Turner

CTO & Co-Founder
leigh@multikor.ai

Serial founder and inventor with 25+ years designing and scaling high-performance distributed systems and cloud-native platforms.

Patents & Innovation:

  • • Holds multiple U.S. and international patents in advanced networking and distributed architectures
  • • Core foundations for modern AI and data-intensive platforms

Technical Expertise:

  • • Architected large-scale, mission-critical systems across AI, cloud, and SaaS
  • • Built enterprise-grade agentic AI platforms, hyperscale microservices, global data infrastructures
  • • Integrated LLMs, RAG systems, and developer enablement frameworks to operationalize AI securely at scale
Anthony Antonuccio

Anthony Antonuccio

SVP, Business Operations
anthony@multikor.ai

Seasoned operator with 35+ years of strategic leadership in technology, product, and go-to-market execution, blending operational rigor with strategic vision.

Successful Exits:

  • Valent Software: Co-founder → Acquired by Lycos
  • Vivo Software: Co-founder → Acquired by RealNetworks
  • • Leadership roles at Amazon AWS and Novell

Track Record:

  • • Built and scaled products used in 130+ countries
  • • Led market expansion initiatives delivering 10X growth in membership, revenue, and penetration
  • • Specialized in aligning product strategy, SaaS/cloud solutions, business development, and GTM execution
Senior AI Architect

Senior AI Architect

Senior AI Architect with 13+ years designing and operationalizing enterprise-grade AI, cloud, and MLOps platforms. Lead architect for SLM hierarchy, Neptune RAG, and hybrid DAG orchestration.

Technical Expertise:

  • • Led architecture of LLM, RAG, and AI/ML delivery pipelines using AWS Bedrock, SageMaker, Databricks
  • • Lead architect for 4-Tier SLM Hierarchy, Neptune RAG knowledge graph, and hybrid DAG orchestration
  • • Domain-specific SLM training infrastructure design and deployment
  • • Cloud-native CI/CD frameworks and production-grade AI operationalization

Compliance & Security:

  • • Expertise in DoD, NIST, HIPAA, SOC2 certified deployments
  • • Turns advanced AI capabilities into secure, scalable, governable production systems
  • • Focus on model reliability, cost transparency, and operational performance at scale
J. Scott Benson

J. Scott Benson

Board Chair

$500K investor in Multikor and founder of software.com, bringing deep expertise in business development and strategic partnerships.

Key Contributions:

  • $500K Investor: Significant personal investment in Multikor, aligning board governance with skin-in-the-game commitment
  • Founder, software.com: Proven track record building and scaling software companies
  • Business Development: Deep expertise in strategic partnerships and go-to-market execution
  • Board Governance: Board-level governance and investor relations leadership

Team Expansion Plan

Q1 2026
12 People

4 executives + 8 developers

Key GTM Milestone
Q2 2026
18 People

First Sales Hire (AE) + 2 CSMs, 2+ engineers, 1 Ops Manager

De-risked: Founder-led sales builds $2M pipeline before AE joins. AE inherits qualified opportunities.

2027 (Post Series A)
25-30 People

Scale: 5-6 AEs, 15 engineers, CSM team

2028
50-70 People

Preparing for Phase 2 BPO channel launch

Series A Roadmap

Path from $4.5M seed to $15M-$25M Series A (Q3-Q4 2027)

Seed Stage Goals
(Q1-Q2 2026)

  • • Multikor MVP deployed and operational. Negotiating first customer pilot with Apexon
  • • Close $4.5M seed at $30M pre-money
  • • Achieve $500K-$1M ARR run-rate
  • • Validate product-market fit with 2-5 customers
  • • Prove unit economics (LTV:CAC >20:1)

Growth Phase
(Q3 2026 - Q2 2027)

  • • Scale GTM team (3 AEs, 2 SDRs, 2-3 CSMs)
  • • Scale proven services, first domain SLMs, expand disciplines
  • • Grow to 35-50 customers
  • • Achieve $12M-$15M ARR
  • • Prove 88-91% gross margins at scale

Series A Target
(Q3-Q4 2027)

  • • Raise: $15M-$25M
  • • Valuation: $120M-$180M post-money
  • • Use: Aggressive GTM expansion, geographic scale
  • • Target: $40M-$60M ARR by end of 2028

Post Series A
(2027-2028)

  • • Scale direct sales motion
  • • Full SLM fleet, expand disciplines based on demand
  • • Expand to 120-160 customers by 2028
  • • Begin BPO pilot programs
  • • Build foundation for Phase 2 launch

Exit Scenarios

Multiple paths to exceptional returns

Scenario A: Direct Sales Only (Conservative)

2030 ARR $120M-$180M
Valuation (8-10X) $960M-$1.8B
Seed Investor Return 11-23X
Exit Paths Strategic acquisition, Series B/C

Scenario B: Direct + BPO Channel (Base Case)

2031 ARR $600M-$1.1B
Valuation (10-12X) $1.5B-$3.6B
Seed Investor Return 43-103X
Exit Paths Strategic acquisition, IPO

Strategic Partnerships

NVIDIA Inception Logo

AI Platform Partner

NVIDIA Inception Program Member

  • $100,000 in Approved Credits: Dedicated GPU compute credits for AI model training, LLM fine-tuning, and advanced inference workloads
  • AI Platform Access: Access to NVIDIA's latest AI SDKs, developer platforms, and cutting-edge GPU technology
  • Technical Training: Free self-paced courses, discounted expert-led workshops, and personalized tool recommendations
  • Preferred Pricing: Special pricing on NVIDIA hardware and software, plus exclusive partner offers and free cloud credits
  • Venture Capital Network: Exposure to NVIDIA's VC network through Inception Capital Connect and curated networking events
  • Go-to-Market Support: Official badges, co-branded marketing assets, and access to NVIDIA's global networks

Investor Insight: NVIDIA Inception membership validates our AI-first architecture and positions Multikor within NVIDIA's ecosystem of high-potential AI startups. The $100K in credits accelerates our Domain Language Model development and reduces capital requirements. This relationship provides both technical acceleration (access to latest AI platforms) and strategic positioning (NVIDIA VC network access and co-marketing opportunities).

AWS Logo

Cloud Infrastructure Partner

AWS Activate Program Partnership

  • $50,000 in AWS credits ($10K received, $40K pending approval - 2 installments in Q2 and Q3 2026)
  • Financial Impact: Extends seed capital runway, reduces infrastructure burn by ~$4K/month
  • Technical Support: Access to AWS technical resources, Bedrock optimization, and architecture reviews
  • Go-to-Market Support: AWS co-marketing opportunities and customer introduction programs
  • Strategic Validation: AWS partnership validates our cloud-native architecture and positions us for deeper integration with AWS AI services

Investor Insight: AWS partnerships are typically reserved for high-potential startups with validated technology and strong market fit. This relationship provides both capital efficiency improvements and strategic positioning within the AWS ecosystem.

Apexon Logo

Strategic Partner — Pilot in Negotiation

Apexon: Strategic Partner — First Customer Pilot in Negotiation

  • Pilot Partnership: First customer pilot in negotiation — agentic customer support for outsourced operations
  • Technical Expertise: 5,500+ digital engineers with deep expertise in Agentic AI, cloud-native platforms, and intelligent automation
  • Pilot Validation: Real workflow data to train first domain-specific SLMs
  • Enterprise Experience: 28+ years building enterprise-scale platforms with proven AI/ML capabilities
  • Strategic Backing: Backed by Goldman Sachs Asset Management and Everstone Capital, validating enterprise-grade partnership

Investor Insight: Multikor deployed the MVP independently. We are now negotiating our first customer pilot with Apexon, validating our BPO concurrent strategy. Real enterprise workflow data will train domain-specific SLMs. Their 5,500+ engineers and Goldman Sachs backing validates enterprise-grade partnership.

Industry Confirmation

Market Validation

"Red Hat confirmed our approach is uniquely productizing AI for SMBs who don't have AI budgets in place."

This validates our autonomous automation model — SMBs buy operational outcomes, not AI software.

Total Strategic Partner Investment: $150,000 in credits

(AWS $50K + NVIDIA $100K) - Counting towards first seed investment

Strategic Acquirer Interest

Cloud Platforms

AWS, Microsoft Azure, Google Cloud (add AI automation to their stacks)

Enterprise Software

ServiceNow, Salesforce, SAP, Oracle (augment their platforms)

AI Platform Leaders

Anthropic, Google, StackAI (AI-native platform acquisition)

BPO Providers

Accenture, Cognizant, Genpact (embedded in their operations)

PE Firms

Roll-up play for enterprise automation category

Why the BPO Channel Creates Outsized Value

Multiplier Effect

Each BPO = 10-100 enterprise clients reached

Embedded Operations

Massive switching costs = defensible moat

Network Effects

Winner-take-most market dynamics at scale

Valuation Premium

BPO platform commands 10-12X vs. 8-10X for direct sales

Strategic Value

Buyer gets access to entire BPO provider ecosystem

Why Invest in Multikor AI Now?

1

Massive Market with Clear Pain

$500B+ TAM across enterprise and SMB automation. Additional $245B complementary BPO channel opportunity. Enterprises waste billions on fragmented, ineffective automation. Proven 50-60% cost reduction = urgent CFO/COO priority.

2

Phased Approach Reduces Risk

Phase 1 (2026-2028): Validate with direct customers ($500B TAM). Phase 2 (2027-2028): Scale via BPO channel ($245B complementary TAM). Multiple paths to exceptional returns (Phase 1 only = 24-45X conservative, Phase 1+2 = 150-330X base case).

3

Differentiated Technology

Domain-specific SLMs trained on real workflow data. 4-tier model hierarchy with 70% at ~$0 cost. 20+ methodology guardrails. Self-healing with 24 feedback loops.

4

Exceptional Unit Economics

Phase 1: LTV:CAC of 20-100:1, payback in 2-6 months. Phase 2: LTV:CAC of 200-1,000:1, payback in 1-3 months. Gross margins: 88-93%. Success-based pricing = customer-aligned incentives.

5

Capital Efficient Path to Scale

$4.5M seed → $12M-$15M ARR → $15M-$25M Series A (Q3-Q4 2027) in 18 months. Fast-fail philosophy with monthly decision points. Lean team of world-class technical and business leaders. Proven founders with track record in enterprise SaaS and AI/ML.

6

Multiple Expansion Vectors

Discipline Expansion: AP + CS (2026) → Procurement, HR, Kaizen (2027+). Customer Expansion: 125-140% net revenue retention. Market Expansion: SMB → Mid-market → Enterprise. Geographic: U.S. → UK/EU → APAC. Channel: Direct → BPO providers (10-100X multiplier).

7

Clear Path to Unicorn+ Status

Phase 1 alone: $120M-$180M ARR by 2030 = $1B+ valuation. Phase 1 + Phase 2: $600M-$1.1B ARR by 2031 = $6B-$13B valuation. Strategic acquirer interest from cloud platforms, automation vendors, and BPO providers.

What Kills This?

Every investment has risks. Here's what we're watching and how we're mitigating.

Big Tech Commoditization

Risk: Anthropic, Google Vertex AI, StackAI ship competitive enterprise solutions.

Mitigant: Domain-specific SLMs trained on real workflow data can't be replicated generically. Methodology guardrails require deep domain expertise.

📈

SLM Development Timeline

Risk: SLM training takes longer than projected.

Mitigant: 4-tier hierarchy: LLMs handle all tasks initially. SLMs progressively take over as trained.

Pilot Failure Risk

Risk: Apexon customer pilot doesn't deliver expected results.

Mitigant: JTBD methodology identifies real pain. 24 feedback loops adapt in real-time. MVP already operational, de-risking technical delivery.

👥

Infrastructure: Neptune Costs

Risk: Neptune Analytics at $184/day (80.9% of infra).

Mitigant: Breakeven at 5 clients. NVIDIA credits offset training. SLM inference cheaper than LLM.

💰

Capital: Runway & Series A

Risk: Don't hit $12M-$15M ARR milestone for Series A. Market conditions tighten.

Mitigant: $4.5M seed. Cash flow positive at 5 clients. 24+ month runway. Multiple exit paths.

LLM Dependency During Transition

Risk: Reliance on third-party LLMs before SLMs are ready.

Mitigant: Cloud-agnostic (AWS/Azure/GCP). LLM costs declining 10X/year. SLMs progressively reduce dependency.

The Ask

$4.5M Seed Round

We're raising $4.5M at a $30M pre-money valuation (13% equity) to validate our pilot-driven strategy, train first domain SLMs, and achieve $12M-$15M ARR for Series A by Q3-Q4 2027.

Investment Amount
$4.5M
13% equity
Target ARR
$12M-$15M
By Q3-Q4 2027
Projected Returns
11-23X
Conservative
⌘K
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