Product / KynticAI Fortress
The sovereign runtime where the Rust engine and LanceDB analyse exact relationships fast.
Enterprise/Fortress is the private commercial runtime for teams that have proved the free open-source Scout path and now need customer-controlled connectors, governance, identity, credential control, an on-prem relationship store, LanceDB vector database, and the proprietary Rust relationship/weighting/traversal engine. Its LLM boundary is simple: Fortress supplies top-example JSON to the customer's own chosen LLM, such as ChatGPT Enterprise, an OpenAI-compatible endpoint, or an internal model.
Store the relationship sets inside your walls, run the Rust/LanceDB analysis there, then send JSON to your chosen LLM.
Buyer spark
This is where private data becomes private advantage.
Fortress is the moment the enterprise buyer sees the moat: the relationship engine runs close to their systems, compares the patterns fast, and hands their approved LLM the evidence it was missing.
The customer keeps the data estate and model estate they already trust.
Rust/LanceDB turns millions of relationship sets into ranked next-task JSON.
The LLM stops guessing from fragments and starts explaining from governed evidence.
Plain English
What Fortress does and how the relationships support the next task.
What it does
Enterprise/Fortress runs the private Rust engine and LanceDB vector database around the Universal Context Layer (UCL) for exact authorised enterprise data.
How it works
It runs close to the customer's systems, reads approved records and source structure, stores attribution paths and relationship sets, analyses them with the Rust engine/LanceDB database, and serves governed JSON without making an external hosted service the data owner.
Commercial value path
It gives security-conscious buyers a serious enterprise path: fast relationship analysis, private data control, and JSON output their own LLM can explain.
Task moment
Your chosen model, including ChatGPT Enterprise or an internal LLM, can explain the next task while sensitive data and the relationship store stay under your control.
What you get
The concrete deliverables behind Fortress.
Private runtime plan
Deployment shape for a customer-owned data plane, including where connectors, one-off import packs, source access, the Rust engine, LanceDB vector database, JSON output, and audit controls live.
Exact-data connector scope
A governed map of approved systems and fields while credentials and raw operational records stay under customer control.
Proprietary Rust/LanceDB relationship engine
Relationship, weighting, traversal, recency, contradiction, similar-pattern, LanceDB vector similarity, and confidence scoring before the LLM drafts the next task.
High-load vector runtime
The enterprise path is for millions of relationship/vector records, concurrent search, production observability, and deployment-specific P95/P99 performance targets rather than Scout's proof-scale PostgreSQL/pgvector path.
Governed JSON handoff
Relationship analysis output with provenance, purpose, role controls, caveats, probabilities, and audit trails for the customer's own model endpoint.
Example data walkthrough
Fast relationship analysis across CRM, support, usage, billing, and outcome signals
Privacy-safe synthetic example backed by a real validation path. Private connector scope, source permissions, and governance are confirmed per pilot.
01 / Private signals
Fortress reads permitted structure in place
email = samira.patel@example.invalid
support_ticket = API timeout
usage_14d = down 29%
billing_status = active
crm_contact = renewal sponsor
The exact authorised operational facts stay inside the customer-controlled runtime.
02 / Governed relationship
Rust links the relationship pattern
attributionPath = ticket -> usage_drop -> billing_active -> renewal_risk
churnRisk = rising
supportDrag = high
similarSavedPattern = resolved support + usage recovery
sourceTrail = CRM + support + usage + billing
The Rust engine and LanceDB vector store can compare this account with similar saved and lost relationship sets without exposing raw source records to KynticAI product operations.
03 / Money move
Customer success gets a next task
recommendedAction = senior engineer response + account-owner call
confidence = 0.81
value_target = reduce churn probability
handoff = JSON to customer LLM
The engagement is framed around relationship-backed retention action, not a guaranteed outcome.
How it works
The enterprise-grade sovereign relationship engine
Enterprise/Fortress takes the free open-source Universal Context Layer (UCL) data-plane foundation from Scout and hardens it for private enterprise operation. Private connectors and approved import packs read source structure under customer control, the on-prem relationship/LanceDB vector store keeps governed data items close, the proprietary Rust engine links and weights relationships, and JSON output carries provenance back to its source before the customer's chosen LLM explains the task.
Private connectors and imports
Read SQL Server, PostgreSQL, REST/CRM, email, document, enterprise system metadata, and customer-approved one-off imports through the agreed deployment path.
Relationship sets and LanceDB
Persist identity links, attribution paths, source order, semantic vectors, and relationship sets inside the customer-owned LanceDB-backed runtime.
Rust engine, policy, and provenance
Apply proprietary Rust relationship weighting/traversal, LanceDB vector similarity, identity, role controls, confidence scores, temporal decay, audit export, and source trails to every generated fact.
JSON to your LLM
Send the relationship output to the customer's approved LLM endpoint, for example ChatGPT Enterprise, an OpenAI-compatible gateway, or an internal model.
Sovereign operation
Scope deployment for the customer VPC, private infrastructure, Kubernetes estate, or restricted environment with controlled updates and support paths.
What this unlocks
The practical moves that make Fortress worth paying for
Private connectors
Bring enterprise-only systems into the relationship memory while keeping credentials and raw records in customer-controlled vaults and data stores.
LanceDB scale path
Move beyond Scout's PostgreSQL/pgvector proof store into a high-load vector path for large relationship sets, concurrent search, and customer-specific performance validation.
Governance views
Show source trails and relationship usage without turning the product into an untracked data copy.
Identity integration
Align evidence access with OIDC, SCIM, SAML, RBAC, and enterprise support workflows.
Customer LLM handoff
Deliver source-traced top-example JSON to the customer's own model layer, rather than bundling a KynticAI model inside Fortress.
Operational hardening
Package the data plane for deployment, update channels, audit trails, health checks, and scoped support paths.
Integration points
Designed to sit inside the enterprise stack you already own
Enterprise data
Pilot-scoped SQL, CRM, ERP, document, API, email, and storage systems with connector status verified per engagement.
Security estate
Credential vaults, customer identity providers, role controls, source trails, audit paths, and private deployment topology.
Model layer
Customer-owned LLM endpoints such as ChatGPT Enterprise, OpenAI-compatible gateways, internal agent platforms, GraphQL clients, REST consumers, and BI workflows.
Back to the platform story