The platform

Four products.
One operating body.

Each product delivers standalone value from day one. Together they form a complete AI-ready operating system — built on top of what your business already has.

01 Bloodstream → 02 Skeleton → 03 Muscles → 04 Immune System →
Data Bloodstream
Data Engine Room
Clean, governed, AI-ready data. Always current.
Process Skeleton
Process Scaffolding
Every workflow mapped, automated, auditable.
Agentic Muscles
Agentic Engine
AI agent teams that execute and deliver outcomes.
Immune System
Pruning Engine
Models that improve with every run. Governed.
— Nexin Systems layer above your stack —
Salesforce NetSuite HubSpot SAP + 500 more
Modular by design

Buy what you need. Each product stands alone and delivers value from day one. Start with the Data Engine Room, prove the value in 4 weeks, and expand when ready. No monolith. No lock-in.

Custom, not configured

Off-the-shelf platforms give you software and a manual. We deliver a solution built around your data, your processes, and your specific AI objectives. The platform is the engine. The solution is bespoke.

The integration is the product

Bloodstream feeds Skeleton. Skeleton orchestrates Muscles. Muscles improves through the Immune System. Each product compounds the others. That flywheel is what no point solution can replicate.

Vendor-operated infrastructure

Databricks, Azure, Airbyte — all vendor-operated. Clients bring their data. We bring everything else. No cloud contract required, no data engineering team, no integration project to manage.

01 — Data Bloodstream

Data Engine Room

Connects every system. Cleans everything. Delivers AI-ready data.

The bloodstream carries what the body needs to function. Without it, nothing works. The Data Engine Room is the same — it connects every source system, cleans and unifies your data, and delivers AI-ready Master Data to every downstream system. Your AI is only as good as the data underneath it. We fix the foundation.

Data is everywhere — and nowhere
CRM, ERP, databases, spreadsheets. No single source of truth. Every team has a different number for the same metric.
AI projects stall at the data layer
60% of enterprise AI projects fail due to data quality. LLMs amplify bad data catastrophically. This is the #1 AI blocker.
Data means nothing to AI without semantics
Even clean data fails LLMs without context. 'ARR', 'revenue', 'bookings' all mean different things. Without an ontology, AI guesses.
Talk to us → See live demo →
DATA BLOODSTREAM — ERYTHROCYTE REFERENCE

Medallion pipeline

Bronze
Raw ingestion
Data lands as-is from every source system. Append-only.
↓
Silver
Business logic applied
Rules, cleaning, schema mapping. DQ checks at every field.
↓
Gold
Master Data — AI-ready
Canonical entity tables. Identity-resolved. Semantically enriched.

+ Semantic mesh layer

AI-generated ontology sits above Gold — enabling LLM queries with business-level precision.

Table stakes — ships at launch
✓500+ pre-built connectors via Airbyte OEM
✓Automated DQ: nulls, dupes, type errors
✓Identity resolution across all sources
✓Data lineage + full audit trail
✓Version history and rollback
Moat builders — differentiated
✦AI-generated ontology from Gold table patterns
✦Semantic proximity mesh for LLM queries
✦AI rule extraction from documents and video
✦Vendor-operated multi-tenant Databricks

Suite position

Standalone product — or feeds directly into Process Scaffolding, Agentic Engine, and Pruning Engine as the data foundation for the entire platform.

02 — Process Skeleton

Process Scaffolding

Every business process — mapped, automated, and running.

A skeleton gives a body its structure. Without it, there's no shape — no repeatable form that lets everything else function. Process Scaffolding maps every business workflow and runs it — sequencing AI agent steps, human tasks, ETL, and system calls. Tribal knowledge becomes infrastructure. Every decision is logged. Nothing gets dropped.

Workflows live in people's heads
When key people leave, tribal knowledge leaves with them. Quality degrades silently until something breaks.
Tasks get dropped between systems
Handoffs happen in email. Steps are missed. Nobody has a real-time view of where a process is or what's blocking it.
Nothing is repeatable at scale
Running 3 campaigns is manageable. Running 10 requires a system. The bottleneck isn't people — it's process infrastructure.
Talk to us → See live demo →
PROCESS SKELETON — OSTEON CROSS-SECTION

Example: Campaign brief → launch

Trigger
Campaign brief received
Workflow fires automatically
↓
ETL
Create filters & query data
Bloodstream queried for segment
↓
AI Agent
Write & review copy variants
Muscles agent team executes
↓
Human
Review & approve top 2
Human in the loop — your team
↓
System
Load into campaign manager
Automated handoff to Klaviyo
Step types
✓ETL — data transformation and pipeline steps
✓Human task — assigned review, approval, edit
✓AI agent — Muscles agent team as a step type
✓System API — webhook, CRM push, delivery
✓Approval gate — named approver, full audit log

Suite position

Standalone product — or the central orchestration backbone that coordinates every other product in the platform as step types.

03 — Agentic Muscles

Agentic Engine

AI agent teams that activate, execute, and deliver — autonomously.

Muscles are what make the body act. They convert intent into force. The Agentic Engine is the orchestration layer that sits above every AI point solution — building and deploying your own agents, and coordinating third-party agents via A2A protocol. Tasks that took teams hours, agents handle end-to-end. Humans review key outputs. Everything else runs automatically.

Point solution agents don't talk to each other
Salesforce, ServiceNow, HubSpot — each has its own AI agent. Each operates in a silo. No cross-platform handoff.
Agents complete tasks, not workflows
An agent can write an email. A complete campaign requires 12 interconnected steps. Single agents can't close that loop.
Nobody can see what agents are doing
When 10 agents run across 4 systems, visibility collapses. Auditability is an afterthought — not designed in.
Talk to us → See live demo →
AGENTIC MUSCLES — SARCOMERE STRUCTURE

Agent team structure

Manager
Objective decomposition
Receives the task. Breaks it down and directs the team.
↓ delegates ↓
Reviewer
Quality control
Checks every output before it propagates. Flags issues.
↓ checks ↓
Operator
Task execution
Focused, autonomous, accountable. Executes and returns outputs.
A2A protocol — the differentiator
✦Linux Foundation open standard — Google, Microsoft, Salesforce, AWS
✦Any agent, any platform — Salesforce → Google → ServiceNow
✦Typed task contracts — structured input/output per agent call
✦Unified observability across own and third-party agents

Suite position

Standalone product — or plugs into Process Scaffolding as an AI agent step type, triggered by the workflow and returning outputs automatically.

04 — Immune System

Pruning Engine

Every model in your business — improving with every run.

The immune system detects what isn't working, corrects it, and keeps everything healthy. The Pruning Engine does the same for your AI models. It takes any LLM from base to production and keeps it improving — using the latest fine-tuning methods so the technology does the heavy lifting. It ships model improvements like software releases: versioned, human-approved, deployed with a single action.

Models degrade silently after deployment
Drift happens. Use cases change. Most organisations have no systematic way to detect when a live model is underperforming.
Fine-tuning requires research expertise most teams don't have
DPO, GRPO, LoRA, RLHF — the methods that produce the best models require ML research skills most mid-market teams don't employ.
No governed path from evaluation to production
Evaluation and deployment are disconnected. No formal promotion gate, no human sign-off record, no audit trail.
Talk to us → See live demo →
IMMUNE SYSTEM — T-CELL / B-CELL / NK-CELL

7-stage model lifecycle

01
Base input
›
02
Eval builder
›
03
Fine-tune
›
04
Version control
05
Production gate
›
06
Production
›
07
Post-prod monitor

Stage 05 — Hard gate

Human sign-off required. No exceptions. Named approver. Immutable audit trail. No model enters production without approval.

Fine-tuning methods
✦SFT — supervised fine-tuning on labelled pairs
✦DPO — preference-based training
✦GRPO — verifiable reward-based training
✦LoRA — parameter-efficient fine-tuning
✦Synthetic training data generation

Suite position

Wedge product for any model rollout — or feeds fine-tuned models directly into every other product in the platform. Every run's learning compounds into the next.

Your business already has the brains.
We give it the body.

Start with one product. Prove value in 4 weeks. Expand when ready. Our Field Delivery Engineers do the work — you get the outcome.

Talk to us → How we work →