Patent pending · 3 provisional filings · 11 trade secrets

OneAIforallyourenterprisesystems.

Governed at the field level. Model-agnostic. Replaces Agentforce, Now Assist, Joule, and Copilot with one platform at roughly 1% of the multi-vendor cost.

Multi-vendor stack / 50K users

$0M/yr

AIGIS / 50K users

$0.0M/yr

typical, all-in

Savings

0×

vs the multi-vendor stack

The problem

Every vendor wants you locked in.

The big enterprise vendors are racing to charge per-conversation tolls on data you already own. The math gets ugly fast.

Vendor lock-in

Agentforce only sees Salesforce. Joule only sees SAP. Now Assist only sees ServiceNow. Every system wants to sell you a different AI for the same data.

Cost explosion

$2 per conversation across 50,000 users equals $180M per year. That isn't AI economics. That's a vendor toll booth.

Theatre security

Most AI products mask sensitive fields with [REDACTED] tokens. The model still knows the field exists. Stripping is the architecturally correct answer.

The solution

One brain. Every system. Your permissions.

AIGIS is governance middleware. It sits above your enterprise systems and below your AI of choice, and it enforces native security on every query and every write.

One brain.

AIGIS classifies intent, routes queries, and merges results across systems. The model never sees raw data. Only what you're allowed to see.

Every system.

Salesforce, SAP, ServiceNow, Postgres, Snowflake, BigQuery. Same governance pipeline. Cross-system queries in parallel.

Your permissions.

We don't replace your security model. We enforce it. Three tiers per system, live record access, never cached.

How it works

Live everything. Cached nothing that matters.

AIGIS never copies your data. Permissions are cached for speed, record access is checked live on every query, and every decision is logged in the provenance ledger.

01
User
asks a question
02
System Widget
SF / SAP / SNOW chat
03
AIGIS MCP
the brain
AIGIS
04
Permissions
cached + live
05
Target System
live query
06
LLM
any model
07
Response
filtered + provenance

Read path

Live SOQL, live OData, live SQL. Permission cache for speed, live record access for safety.

Write path

Human-in-the-loop. Permissions re-verified at confirmation time, not just at proposal time.

LLM path

Claude, GPT, Gemini, or your own. Swap on Friday. Failover is automatic.

The math

The real enterprise stack costs $50M to $200M /yr.

Most enterprises don't run one AI vendor. They run several. Here's the public 2026 pricing for the typical multi-vendor stack at 50,000 users.

Vendor (50K users)
Pricing model
Annual cost
Agentforce Employee Add-On
$125 to $150 / user / mo
$75M to $90M
ServiceNow Now Assist
$50 to $100 / fulfiller / mo
$30M to $60M
SAP Joule Premium
Per AI Unit, consumption
$2M to $20M
Microsoft 365 Copilot Enterprise
$30 / user / mo
$18M
MuleSoft (cross-system enabler)
Annual platform license
$2M to $5M
Stack total
Real enterprise reality
$127M to $193M
AIGIS Scale (3 systems, all-in)
Platform plus add-ons
$600K to $1.5M

Sources: Salesforce, ServiceNow, and Microsoft public 2026 pricing. SAP Joule and Now Assist pricing under NDA, ranges based on published industry estimates. Agentforce Flex Credits at $0.10 per action are an alternative model with similar order-of-magnitude cost at scale.

The defensible moat

Most AI masks. AIGIS strips.

Masking protects the value of a field. Stripping protects the existence of the field. The difference is architectural, and it shows up the moment a model is asked to reason about your data.

Industry default

Masking

What the LLM sees:

  • Account.NameAcme Corp
  • Account.AnnualRevenue[MASKED]
  • Contact.SSN__c[MASKED]
  • Account.OwnerJ. Smith

The model still knows SSN__c and AnnualRevenue exist. It can reason about their position, infer relationships, and leak structural metadata in its response.

AIGIS approach

Stripping

What the LLM sees:

  • Account.NameAcme Corp
  • Account.OwnerJ. Smith
  • fields the user cannot access are architecturally absent

The model has no way to know SSN__c exists. No metadata leakage. No structural inference. The data is architecturally absent before the prompt is constructed.

For the technically curious: Salesforce Agentforce honors object and field-level security at query time. AIGIS adds a second layer that removes fields from the prompt context before the LLM ever sees them, so model output cannot leak structural metadata. Both approaches enforce permissions. Only one enforces them on the model itself.

Why AIGIS wins

Four things vendors structurally can't match.

Each pillar is rooted in either a published patent application or an architectural decision a single-vendor AI cannot replicate without cannibalizing its own revenue.

Model-agnostic

Use Claude, GPT, Gemini, or your own. Swap on Friday. Automatic failover means no single LLM outage takes down your business.

Cross-system

Ask once. Get answers from Salesforce, SAP, ServiceNow, and your data warehouse in parallel, with per-system permission provenance.

Human-in-the-loop writes

AIGIS never writes without your explicit confirmation, and re-verifies your permissions at confirmation time, not just at proposal time.

Zero vendor lock-in

Cancel any time. Your data never leaves your systems. We don't store it. We govern it. Your security model stays the source of truth.

Defensibility

Built to be defensible.

A patent portfolio across observable behavior, plus eleven trade secrets protecting the internal architecture. Some forms of intellectual property are stronger when they never become public.

0

Invention disclosures

0

Provisional patents pending

0

Trade secrets

Filing 01

Data governance methods

Permission enforcement on AI prompt construction across heterogeneous enterprise systems.

Filing 02

Write-path safety

Mechanisms that keep AI-generated mutations governed at confirmation time.

Filing 03

Multi-system orchestration

Routing intent across multiple systems while preserving each system's native security posture.

Design partner program

We're accepting 5 enterprises for 2026.

AIGIS is a managed engagement, not a self-serve sign-up. We do the work alongside you. We're capping the year at five so we can give each partner the depth they need.

Slots remaining

04 / 05

Cohort

2026 Q2 to Q4

  • We deploy AIGIS into your environment, whether Salesforce, SAP, ServiceNow, or your data warehouse
  • We configure your permissions, tune the AI to your data, and harden the integration
  • We run it for you for the first six months, fully managed
  • You get exclusive 2026 design-partner pricing and direct line to the founder

Average deployment timeline: 2–4 weeks · First read-only queries within 48 hours

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