The compounding layer

Models deprecate every quarter. Your enterprise knowledge compounds for years with Next Moca.

The model layer turns over. Workflows, audit history, governance, and your team's institutional memory do not. Next Moca is the durable layer above whichever model wins this quarter. Build once. Compound forever.

Talk to founders → Read the thesis
Stop selling hours

You don't scale a services firm by hiring engineers. You scale it by shipping a product.

Next Moca turns the agentic engagements your team already delivers into a product your customers subscribe to. Same code, same workflows. Reusable, audited, ownable. Services revenue compounds into product revenue.

Turn your delivery into a product → See how it works
Agent control plane · System of record

Hyperscalers sell agent infrastructure lock-in. We let you ship agentic products in weeks. Without locks.

Turnkey white-label agent control plane for the new intelligence agencies. Models swap with one config change. Your IP never leaves your VPC. Workflows, audit history, and governance compound for years.

Talk to founders → See the architecture
For the new intelligence agencies

OpenAI and Anthropic hired big consulting firms. Yet, they cannot service all your customers.

OpenAI acquired a 100-million dollar company built in 18 months. They cannot buy them all. Next Moca is the platform AI agencies use for shipping agentic products and services in weeks. Without the risk of acquisition exit dependency.

Build your AI agency on Next Moca → See the architecture
500M+Tokens consumed in labs and pilots
1,000+agents capacity per tenant
Backed & built with
The thesis

Every enterprise tool was built for a world where humans did the work.

Now humans build the agents.

Agents do the work.

Next Moca is the operating layer for both.

The compounding layer

Primitive-makers scale the substrate. Vertical experiences compound elsewhere. AWS sold compute. A decade of B2B SaaS (Wistia, Basecamp, Mailchimp) built the durable layer on top. The same economic structure keeps model providers focused on the model layer. The control plane is where your governance, workflows, and institutional memory live. That layer should compound, not reset.

Models deprecate. Your enterprise knowledge compounds.

Models deprecate every quarter

Three weeks in April 2026 reshaped every AI roadmap. Foundry, Bedrock Managed, Gemini Enterprise, Claude Managed each lock to one cloud and one model family.

GPT-4 Claude 3.5 Gemini 1.5 GPT-5 Claude 4.6 Gemini 3 ?

Workflows, audit, governance compound for years

What you build above the model layer survives every model turnover. Your IP, your customer trust, your operating record. Build once. Compound forever.

Governance & audit ledger+years
Workflows & HITL gates+years
Domain knowledge & memory+years
Models & runtime~quarter
80%+
Time compression · 12 months collapses to 4 weeks
90%+
Cost reduction · vs. assembling the layer in-house
∞
Workflows, audit, governance · yours forever
Three pillars

The structural decisions that make the control plane the durable layer of the stack.

01 · Sovereignty

Your IP never leaves your VPC.

Architectural and contractual. The Federation Model is written into the customer MOU, not just the diagram. Your data, your models, your tenants, your trust boundary.

VPC-resident runtime · BYO model endpoints · contractual data isolation · no cross-tenant training

02 · Neutrality

One-click A/B across any model.

Clone an agent. Run two models on the same input. Version any workflow step. A first-class workflow primitive, not a config flag buried in YAML.

OpenAI · Anthropic · Gemini · Bedrock · Foundry · self-hosted · swap with one config change

03 · Compounding

Knowledge compounds. Models deprecate.

Workflows, audit trails, HITL playbooks, evaluators, governance. Build once. Compound forever. Every agent, every action, fully ledgered.

Append-only ledger · workflow versioning · evaluator graph · ADL spec

Built for the new intelligence agencies

The companies whose proprietary domain IP is the moat. Their host ecosystem ships data primitives but not action primitives. They need a control plane to turn intelligence into product.

Embedded Agent Intelligence Providers

Ship agentic products under your brand. In weeks.

Your domain IP is the moat. Don't burn six engineers and twelve months reinventing orchestration. White-label the control plane, keep your IP in your VPC, embed agents in the product your customers already buy.

  • White-label UI and API surface
  • Per-tenant isolation and governance
  • Federation Model for IP residency
  • Snowflake & Salesforce Native App ready (Q2-Q3 2026)

Founding white-label customer: Aurivio AgentBase · live in production · 1,000 agent capacity per tenant

Agent Service Providers

Deliver agentic engagements that compound across clients.

Every engagement makes the next one cheaper and faster. Standardize on one control plane across your book of business. Reusable, audited, ownable. Your delivery teams ship faster. Your clients see governance from day one.

  • Reusable agent and workflow library
  • Multi-client governance and segregation
  • Audit-ready delivery on day one
  • GCC ops & outsourcing patterns built in

Active with 2 GCC channel partners · 3 US ops pilots · digital workforce playbook

What you're being sold

The category got crowded in April 2026. Most of what shipped is a managed runtime priced in vCPU-hours. We are not that.

Hyperscaler managed agents DIY orchestration (6 engineers · 12 months) Next Moca
Cross-platform reach One cloud. Their ecosystem. Whatever you wire up Cross-3P-platforms by default
Model swap Within their family Refactor your codebase One config change
IP residency Their VPC Yours, if you build it Your VPC. Federation Model.
Time to first production agent Quarters 12 months Weeks
Audit & HITL Add-on Build it First-class primitives
Brand surface Theirs Yours, after twelve months Yours. White-label, day one.
Founding white-label customer

Aurivio AgentBase, powered by Next Moca.

Multi-year white-label MOU signed April 2026. Live in production under Aurivio's brand. Aurivio's IP stays in Aurivio's infrastructure under the Federation Model.

Capacity for one thousand agents per customer (25 commercial users x 40 agents per user). Published category language co-articulated with our founding customer.

1,000
Agent capacity per tenant
Multi-year
White-label MOU · April 2026
"

Most agentic AI today is a black box. AgentBase is the opposite. Agents your team builds. Agents your team owns.

A
Aurivio AgentBase
auriv.io · Snowflake + AWS + Next Moca
What you actually get

The primitives that make the control plane the durable layer. Built for governance, neutrality, and brand sovereignty from day one.

Control plane
Operate
Every agent, every action, fully ledgered
  • HITL approval queues with role-aware routing
  • Append-only audit ledger and rollback
  • Workflow versioning and one-click A/B across models
  • Evaluator graph for continuous quality
  • 116 REST endpoints · SSE streaming · webhooks
Read the architecture brief
White-label · Federation Model
Embed
Your brand. Your VPC. Your customers.
  • White-label UI, API surface, and naming
  • Federation Model · IP stays in your infrastructure
  • Snowflake & Salesforce Native App (Q2-Q3 2026)
  • Per-tenant isolation and governance
  • Co-articulated category language available
Request MOU template
Open source

Open standards and tools for governed agent systems.

Tool layer

Tool Forge. Published on arXiv.

An open-source system for generating governed agent tools and serving the right tools through a token-optimized MCP router. Build reusable capabilities without turning tool catalogs into prompt noise.

View Tool Forge → Read foundation →
Definition layer

Agent Definition Language. Published on All Things Open.

A declarative spec for assembling agents from intent. 90 seconds from prose to a running, observable, governed workflow. Read the article. Read the spec. Fork it.

View ADL spec → Read on All Things Open →

Tools change. Truth doesn't.

Aurivio, May 2026

Twenty minutes is all we need to show you what runs above your hyperscaler. Bring the use case. We bring the live system.

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kiran@nextmoca.com · swanand@nextmoca.com · Boston, MA · Palo Alto, CA