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.
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.
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.
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.
What you build above the model layer survives every model turnover. Your IP, your customer trust, your operating record. Build once. Compound forever.
The structural decisions that make the control plane the durable layer of the stack.
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
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
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
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.
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.
Founding white-label customer: Aurivio AgentBase · live in production · 1,000 agent capacity per tenant
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.
Active with 2 GCC channel partners · 3 US ops pilots · digital workforce playbook
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. |
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.
Most agentic AI today is a black box. AgentBase is the opposite. Agents your team builds. Agents your team owns.
The primitives that make the control plane the durable layer. Built for governance, neutrality, and brand sovereignty from day one.
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.
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.
Hyperscale operators and engineers who built and shipped agentic infrastructure at billion-dollar revenue scale. We are building Next Moca because we know what the next ten years of enterprise AI actually need.

Repeat builder. Co-founded and served as CTO of Green Piñata Toys (acquired). Director of Engineering at Oracle (OCI) and Brightcove, with prior leadership roles at Juniper, Cisco, and others. Built and scaled world-scale services for customers like ByteDance and HBO. Architect behind Next Moca's agentic orchestration and infrastructure layers. MBA (Babson), M.S. Computer Science (Penn State), B.E. Computer Engineering (University of Mumbai).

Product-driven inventor with a track record of bootstrapping new products, blending deep engineering with go-to-market focus. Director of Product at Adobe, with prior leadership roles at Microsoft, Oracle, and others. Holds multiple patents in distributed systems. Architect behind Next Moca's agentic foundations and core AI services. Executive MBA (Michigan Ross), M.S. Computer Science (USC), B.E. Computer Engineering (University of Mumbai).

Engineering and UX leader with 25+ years at Sun Microsystems and Oracle. Founding Member of Technical Staff at Next Moca, leading Agent Experiences. Recognized expertise in UI/UX architecture, data security, and full-stack engineering. Building the intuitive, secure interfaces that bridge human creativity with intelligent automation.
Operators who built and shipped enterprise platforms at billion-dollar scale. They're betting on Next Moca because they've lived the problem we're solving.

Ran product and strategy at Brightcove (CPO) and Ellucian (CPO) over two decades of enterprise SaaS leadership. Now Managing Partner at ND Labs and lead investor in Next Moca.

Head of ML Platform at Capital One, operating production AI infrastructure for one of the largest regulated U.S. banks. Ph.D. in EECS from UC Berkeley, M.S. from UIUC, and B.Tech. from IIT Bombay.
Twenty minutes is all we need to show you what runs above your hyperscaler. Bring the use case. We bring the live system.
In the meantime, you can also reach us directly at kiran@nextmoca.com or swanand@nextmoca.com.
kiran@nextmoca.com · swanand@nextmoca.com · Boston, MA · Palo Alto, CA