Fibinaci A context layer for enterprise AI Apply →
DESIGN PARTNER PROGRAM · OPEN · LIMITED COHORT
§ 00 · Premise 2026

Your data is ready. Your agents are not.

Enterprises spent a decade building world-class data infrastructure. AI agents still cannot reliably navigate it. Fibinaci builds a living map of your data landscape and exposes it securely to your agents, with full sovereignty over what they can see.

§ 01 Industry signal

The industry has spent two years asking why enterprise AI keeps failing in production. The answer is not the model.

Figure i
95%

of enterprise GenAI pilots deliver no measurable P&L impact1

Figure ii
97%

of organizations hit by an AI security incident lacked basic AI access controls2

Figure iii
$670K

added to the average breach cost when shadow AI is involved3

The failure is not the model.
It is the data layer.

References
1MIT NANDA Initiative, "The GenAI Divide: State of AI in Business 2025." Sample of 300 public deployments, 150 executive interviews, 350 employee surveys.
2IBM, "Cost of a Data Breach Report 2025."
3IBM, "Cost of a Data Breach Report 2025." Shadow AI incidents averaged $4.63M versus $3.96M for standard breaches.
§ 02 Where this lands

Fibinaci is in active conversations with engineering and data teams across logistics, enterprise hardware, and software companies. The same problem keeps surfacing in three forms.

Logistics

Agents that need to reconcile across WMS, TMS, and ERP end up writing custom integrations per system.

Each integration carries its own auth, its own PII handling, its own access policy. Quarterly schema changes in any one system break the agent. Typical implementation cycles run four to six months before the first real workflow.

Enterprise hardware

Agents need to span MES and CRM, but compliance will not allow direct access to either.

Manufacturing and customer data live in separate trust zones. Cross-system queries become a months-long compliance review before a single agent ships. The data team becomes the bottleneck for every agent project in the company.

Software & IT services

Agents need to span customer, asset, and procurement systems with different access rules per data class.

Existing identity and access tools were designed for human users, not autonomous agents querying at machine speed. Teams either over-grant access and wait for an incident, or under-grant access and watch agents fail in production.

§ 03 How it works

Fibinaci sits between your data and your agents. No rip and replace. No new pipelines. No changes to existing infrastructure.

01

Connect

Read-only, encrypted connection to your data warehouse. Fibinaci extracts metadata only. Row data never moves.

02

Build the terrain

An AI-enriched map of your data, generated from your warehouse schema. Every entity, relationship, and PII classification. Approved by your team before agents see it.

03

Expose to agents

Your agents connect to a secure MCP endpoint and arrive pre-oriented. They know what data exists, what it means, and what they are allowed to access. Every query is validated before execution.

§ 04 Sovereignty

Your data never leaves your environment. Ever.

i · METADATA ONLY

Structure, not content

Fibinaci extracts table names, column types, relationships, and row counts. Row data is never accessed during terrain construction.

ii · QUERY PASSTHROUGH

Results stream direct

When agents query data, results travel directly from your warehouse to your agent. Nothing is stored or cached at Fibinaci.

iii · PRIVATE NETWORK

No public traversal

Warehouse connectivity uses a private encrypted link. Traffic never traverses the public internet.

iv · AUDIT TRAIL

Every action recorded

Every agent action is logged. You see exactly what was accessed, when, and by which agent, in real time.

§ 05 Design partners

Co-build the category.

We are looking for companies who want to shape this from the ground up. Twelve months of free access. Direct weekly access to the founders. Your use case shapes the roadmap.

What you get
  • Free access for twelve months. No contracts, no risk.
  • Direct weekly access to the founders throughout the build.
  • Your use case shapes the product roadmap directly.
  • First priority on every feature and warehouse integration.
  • Design partner recognition at public launch.
  • Data sovereignty guaranteed.
What we need
  • One technical champion for weekly syncs.
  • A real warehouse environment to build against.
  • Honest feedback throughout the build.
  • A written case study after ninety days in production.

This is the conversation to have now, not in six months. If your company has serious data infrastructure and serious AI ambitions, apply below.