Inject

Any data item

Connectors or approved one-off imports load email addresses, cookies, events, CRM rows, products, support, billing, documents, and outcomes.

Store

Attribution paths

Scout stores each item's relationship set, vector, and ordered attribution path in customer-owned PostgreSQL/pgvector. Fortress moves high-load memory into Rust/LanceDB, not KynticAI product operations.

Compare

Rust + LanceDB

Enterprise contains the proprietary Rust relationship, weighting, traversal, and LanceDB path for fast similarity analysis across millions of relationship sets.

Output

Top-example JSON

The engine creates JSON with the best examples, importance bands, confidence, caveats, and ranked task options for the question being asked.

Explain

LLM task brief

Fortress sends JSON to your approved model boundary. The proposed Elite path shows the executive walkthrough from safe discovery to scoped pilot and outcome review.

Solutions

Private relationship intelligence that scales from one task to many workflows.

Start with free open-source Scout relationship APIs and PostgreSQL/pgvector proof storage, prove one governed task workflow, then expand into Enterprise/Fortress when exact private data, sovereign LanceDB storage, proprietary Rust weighting, high concurrency, and approved model handoff matter. Use the proposed Elite path when executives need the end-to-end discovery, demo, pilot-scope, and outcome-review story.

Buyer spark

One product path, three buyer wins: prove it, scale it, compound it.

The sales story should feel obvious: Scout gets the buyer started, Fortress makes private relationship intelligence enterprise-grade, and the proposed Elite path frames the executive walkthrough as a scoped buying route.

Scout makes the first proof feel low-friction and real.

Fortress makes the enterprise buyer feel safe, sovereign, and in control.

Proposed Elite helps the board see discovery, synthetic demo, pilot scope, and outcome review in one room.

Scout

Free & Open Source

Free, open-source Scout is the Context Engine data-plane path. Deploy locally, inject authorised data items, store attribution paths and vectors in PostgreSQL/pgvector, and expose governed top-example JSON through APIs.

  • Free open-source core selector engine
  • Relationship facts and snapshots
  • PostgreSQL/pgvector proof storage
  • GraphQL and REST API
  • SQLite, REST, and CSV paths
  • React admin console
  • Community support via GitHub

Pilot

Relationship Discovery

Choose a scenario, map the authorised data items, define the governance boundary, and shape the first attribution-path and top-example JSON output.

  • Relationship-analysis walkthrough
  • Connector scenario selection
  • Source-system and role/purpose map
  • Similar-pattern example
  • Confidence and caveat model
  • Next-best-task recommendation
Enterprise path

Fortress

Enterprise Private Runtime

Enterprise/Fortress private runtime for teams that need exact authorised data, sovereign relationship storage, the proprietary Rust/LanceDB relationship engine, and top-example JSON handoff to their approved model boundary or internal models.

  • Everything in Pilot
  • Private connector runtime
  • Proprietary Rust/LanceDB relationship engine
  • LanceDB high-load vector database
  • Relationship JSON to customer LLM
  • Customer-controlled deployment path
  • Identity and governance alignment
  • Credential-vault integration
  • Rollout planning support
  • Custom connector prioritisation

Proposed Elite

Executive Walkthrough Path

Executive walkthrough path that combines Discovery MCP, metadata-only signature approval, synthetic equivalent demo, Fortress pilot scope, approved model boundary, and outcome-review planning where approved.

  • Everything in Fortress
  • Discovery MCP route
  • Synthetic equivalent demo
  • Multi-team rollout planning
  • Bespoke connector engineering
  • Relationship outcome reviews
  • Training and operator enablement
  • Executive value reviews
  • Roadmap alignment
  • Commercial expansion planning
  • Outcome-review rhythm

Why This Model Works

Relationship Infrastructure, Not An AI Wrapper

KynticAI sits between authorised source systems and the model. The product is the private relationship memory: data items, attribution paths, similar relationship sets, and top-example JSON.

JSON Before Generation

The first conversation should produce scoped relationship analysis: data items, attribution path, similar relationship sets, top examples, confidence, JSON handoff, and next task.

Sovereign by Architecture

The product is designed for organisations that need exact-data mode inside their own environment, with KynticAI product operations limited to commercial metadata.

Better Every Day

Approved conversions, losses, support saves, and task outcomes feed the relationship layer so recommendations become more useful over time.

Evidence Results

Relationship analysis in the wild.

Synthetic scenario targets for teams that need reviewable relationship analysis and a better next task, not another platform promise.

KynticAI Result
B2B SaaS Sales

Synthetic revenue scenario - enquiry, content, CRM, product, support, outcome

Show sales what task to do next

A new contact asks about security, searches the compliance page, reviews product B, and resembles converted accounts where a technical proof email came before registration.
KynticAI Result
Subscription Commerce

Synthetic subscription scenario - ecommerce, dispatch, support, churn outcome

Save the customer before churn

Churn spikes in the synthetic set when replenishment arrives more than three days late and the customer has a recent unanswered support question.
KynticAI Result
Manufacturing Quality

Synthetic GMP operations scenario - batch, QC, process signal

A pass can still hide a warning

Batch 2026-0514-L2 passed QC, but endpoint moisture is 0.3% above the process mean and resembles earlier process-drift examples.

Not Sure Which Path Fits?

Start with the evidence demo. It gives the conversation a data-item map, attribution path, governed top-example JSON, and a reviewable next task.

Evidence Results

Solutions work when the next task is backed by the relationship path.

These scenarios show how Context Engine output changes sales, retention, and operations workflows.

KynticAI Result
B2B SaaS Sales

Synthetic revenue scenario - enquiry, content, CRM, product, support, outcome

Show sales what task to do next

A new contact asks about security, searches the compliance page, reviews product B, and resembles converted accounts where a technical proof email came before registration.
KynticAI Result
Subscription Commerce

Synthetic subscription scenario - ecommerce, dispatch, support, churn outcome

Save the customer before churn

Churn spikes in the synthetic set when replenishment arrives more than three days late and the customer has a recent unanswered support question.
KynticAI Result
Manufacturing Quality

Synthetic GMP operations scenario - batch, QC, process signal

A pass can still hide a warning

Batch 2026-0514-L2 passed QC, but endpoint moisture is 0.3% above the process mean and resembles earlier process-drift examples.