Data stuck in silos
Your most important docs, tickets, and research live behind VPNs, so generic AI tools can’t reach them.
Teams need to bring AI to the data, not the other way around.
HedraPrivate AI
Private AI · Secure inference (in build)
Building private AI for confidential and sensitive work.
We’re designing a private AI stack—models, guardrails, and observability—so sensitive work stays under your control once it’s ready.
Prototype in progress—looking for a few regulated teams to co-build with us.
- Status
- Prototype in progress
- Availability
- Invite-only design partners
- Focus
- Data residency & control
Signal Mesh
Designing multi-tenant security with single-tenant trust.
We’re validating an inference mesh that isolates models, storage, telemetry, and secrets per customer. The goal is to propagate policies across every edge and keep data residency intact.
Encrypted context windowsIn design
Adaptive guardrailsResearch
Audit-grade lineageRoadmap
Focus Areas
Pick the use case closest to your workflow.
We’re co-designing with regulated teams across finance, biotech, technology, and healthcare. Hop into the page that matches your priorities to see the roadmap-in-progress.
Finance teams
ExploreWe’re exploring how to handle due diligence, portfolio reviews, and corporate finance analysis without letting deal data leave your stack.
Go to page →Biotech teams
ExploreScoping private AI workflows for ELNs, assay data, and regulatory documentation so sensitive IP stays encrypted.
Go to page →Tech & R&D
ExploreDesigning retrieval across specs, repos, incident notes, and research logs so technical orgs can move faster responsibly.
Go to page →Healthcare operations
ExploreTesting PHI-safe assistants for care coordination, rev-cycle QA, and utilization reviews with full provenance.
Go to page →The Problem
Many AI pilots never reach production.
Sensitive data, unclear security stories, and long vendor reviews often stall progress. Teams want answers, not another platform to babysit.
Security blockers
Legal and IT shut down experiments because nobody can prove where prompts and outputs go.
Leaders need visibility and access controls before they can even experiment.
Slow, pricey pilots
Teams spend months wiring infra and reviewing vendors before the first workflow ships.
Pilots should spin up in weeks with clear pricing—still rare today.
The Hedra Platform
Plan private AI in your environment.
We’re building a managed stack—models, routing, and monitoring—so you can launch use cases fast once requirements are met and still keep ownership of data.
Private clusters
PlannedPlanned single-tenant environments that can run inside your cloud or ours.
Built-in guardrails
PlannedIdentity, logging, and approvals we plan to bake into every request.
Flat pricing
PlannedSimple tiers we’re drafting around capacity, not surprise token bills.
Hands-on support
PlannedSmall team dedicated to launching workflows alongside you once we’re ready.
Deployment options (goal)
Cloud, on-prem, sovereign
Model coverage (research)
LLMs, agents, retrieval, evals
Observability (planned)
Per-request lineage + risk scoring
Use Cases
Use AI where it actually matters.
We’re validating Hedra against real workflows—support queues, financial models, R&D notebooks—while keeping everything private.
Finance teams
In discoveryWe’re exploring how to handle due diligence, portfolio reviews, and corporate finance analysis without letting deal data leave your stack.
Read the use case →Biotech teams
In discoveryScoping private AI workflows for ELNs, assay data, and regulatory documentation so sensitive IP stays encrypted.
Read the use case →Tech & R&D
In discoveryDesigning retrieval across specs, repos, incident notes, and research logs so technical orgs can move faster responsibly.
Read the use case →Healthcare operations
In discoveryTesting PHI-safe assistants for care coordination, rev-cycle QA, and utilization reviews with full provenance.
Read the use case →Contact
Interested in shaping private inference?
Tell us what you’re building and we’ll share our roadmap and next steps within two business days.
- ✓Prioritizing secure deployments in customer VPCs
- ✓Designing integrations that work with your existing tools
- ✓Looking for partners to co-design the first rollouts