A unified platform for AI-powered data products, network intelligence, and document understanding — deployable on your terms, in your environment.
Each module is independently licensable. Run what you need, ignore what you don't.
AI-native workspaces for structured research. Conversations that generate artifacts — not just text. Bring your own LLM backend.
Connect, query, and publish governed data products across heterogeneous sources. DuckDB-powered analytics with a SQL-first interface.
Decentralized peer-to-peer data interchange with a cryptographic audit ledger. Build ontology-defined knowledge networks across orgs.
First-class data application runtime. Deploy AI-driven analytical workflows as purpose-built applications for business users.
Extract, index, and reason over unstructured documents. Semantic search powered by Qdrant vector storage, structured output via LLM pipelines.
Router → Planner → Executor pipeline. Provider-neutral: run Anthropic Claude or Google Gemini. Swap backends without rewriting prompts.
Not a wrapper around an LLM API. A structured system with real layers.
The AI engine uses a three-phase pipeline: Router classifies intent, Planner proposes a structured plan that the user confirms, Executor generates the final artifact. Each phase is decoupled from the underlying model. Swap LLM providers — the prompts, the routing logic, and the output schema don't change.
This means you're not locked to a model vendor's roadmap. When a better model ships, you swap a config value, not a codebase.
Headwaters runs DuckDB in-process against your sources. Queries execute close to the data — no ETL pipeline, no warehouse copy, no replication lag. Data products are governed query views: versioned, permissioned, and composable. The source stays where it is.
When a user asks a question, the answer is computed from live source data, not a stale snapshot loaded into a third system.
Wyatt's peer network has no central broker. Organizations connect directly, governed by a shared ontology. Every data exchange is recorded on a cryptographic audit ledger — tamper-evident by construction, not by policy.
This lets regulated industries share data across org boundaries without trusting a third-party intermediary or standing up shared infrastructure.
Most teams building AI-powered data tooling end up with a chat tool, a BI layer, a data catalog, a network graph, and a document store — each with its own auth, its own user model, and its own ops burden. Huckleberry is one deployment: one auth layer, one admin surface, one license, one schema for all five surfaces.
When a user in Chat references a Data Product, that link is real — not a screenshot embedded in a message.
Three deployment postures to match your security requirements, compliance needs, and operational preferences.
Zero external calls. Cryptographically signed licenses, tamper-evident audit ledger, no usage telemetry. Runs in disconnected environments — SCIFs, regulated infrastructure, or private clouds with strict egress controls.
Deploy in your own cloud or on-premise. Huckleberry phones home for usage reporting and license validation — everything else stays on your infrastructure. You control the data, the runtime, and the backing AI providers.
Fully managed, hosted by Didati. No infrastructure to provision, no patches to apply. Metered by consumption — users, API calls, data volume. Get started in hours.
No proprietary lock-in at the data layer. Standard open-source engines, well-understood operational profiles.
In-process analytical engine. Columnar query performance without a data warehouse. Powers all data product queries and cross-source joins.
Relational backbone. PostgreSQL for production multi-tenant deployments, SQLite for zero-config local or single-tenant installs.
Optional vector store for semantic search and document intelligence. Run alongside the platform or connect an existing instance.
Agent state persistence. Streaming AI agent sessions are durable across reconnects — no state loss on network interruptions.
Connect any supported LLM provider using your own API key. No Huckleberry intermediary in the AI call path — your credentials, your rate limits, your spend.
The agent pipeline decouples routing, planning, and execution from the underlying model. Swap LLM providers without rewriting prompts or changing agent logic.
Administration features that belong in an enterprise platform, not bolted on after the fact.
SAML and OIDC integration. Bring your existing IdP. User provisioning flows from your identity layer, not Huckleberry's.
Scope-based permissions on every resource. Granular read/write/admin separation at the module, object, and operation level.
Org-level groups mapped to permission sets. Manage access at scale without per-user configuration.
Built-in MFA via email and SMS. Enforceable at the org level. No third-party authenticator integration required.
Programmatic access with scoped API keys. Machine-to-machine authentication without session management.
Tamper-evident, queryable audit trail for all administrative and data-access events. Exportable for SIEM ingestion.
Replace Huckleberry's UI chrome with your organization's brand. Full color, logo, and domain customization.
OAuth-based developer app registration. Extend the platform through a governed integration surface with scoped access.
Licenses are signed artifacts. Validation is local and deterministic — no license server dependency in the critical path.
We sell direct. No SDR sequences, no qualification forms. If you're evaluating, email us.