Hast helps enterprises connect private data, internal systems, and expert workflows into governed AI workflows. We combine a secure platform with Forward-Deployed Engineering (FDE) implementation so your AI projects move from prototype to production
Connect existing tools, keep work moving, and deepen business understanding with every collaboration
Set it once, and Agent completes data summaries, operational checks, and reports on time. Whether daily, weekly, or at fixed intervals, recurring work keeps running, with results and execution history available for review.
After connecting the tools your enterprise already uses, Agent can find information, call tools, and move tasks forward within its permissions. Your team keeps working as usual, while each connection can serve more Agents and workflows.
Enterprise context, business rules, and team preferences accumulate through collaboration. Agent starts each new task with the context that matters, reducing repeated explanations and becoming more aligned with your business over time.
Connect enterprise data and core systems so AI agents can carry out real work within controlled boundaries and build business knowledge over time.
Continuous feedback loops that improve quality and performance
Models, tools, and orchestration for planning, action, and recovery
Shared enterprise context across data, systems, policies, and workflows
From customer acquisition and professional work to organizational operations, go deep into diverse business processes and expand step by step from one proven workflow.
Turn user demand and search trends into an ongoing content, distribution, monitoring, and review workflow.
Connect market intelligence and CRM to identify target accounts and move qualified leads forward.
Use customer and product context to diagnose issues, take permitted action, and close the loop.
Use course and learner context to support preparation, Q&A, feedback, and personalized learning.
Understand code and runtime context to advance planning, implementation, review, testing, and troubleshooting.
Connect research and market data to track targets, identify risk, and produce traceable reports.
Handle policy questions, meeting preparation, records, and cross-team follow-up with less repetitive work.
Package a dedicated enterprise Agent as a customer-ready product capability and service entry point.
Continuously observe systems and alerts to diagnose incidents, execute runbooks, and drive review.
Hast's FDE team works directly with your team in real workflows, turning business needs into production systems and continuously improving Agents through co-building, validation, and feedback.
Choose one high-value workflow. Define its users, desired outcomes, success metrics, human owners, and permission boundaries.
Map the relevant files, data, systems, business relationships, and expert knowledge. Define access and authorization.
Design the Agent, its Skills, tools, and workflows. Validate quality and exception handling with real tasks.
Run the Agent in real workflows within clear boundaries. Measure task quality, human collaboration, and business value.
Improve the Agent using real-world results, establish ongoing operations, and expand to more workflows, roles, and teams.
Sustainable enterprise Agent capabilities
Start with one team, then scale across your organization as your workflows, needs, and ambitions grow
Personal workspace with Task Agent included.
Get startedA shared Team workspace with per-seat billing.
Get startedA custom AI workspace for complex operations and deep integrations.
All plans support BYOK (bring your own key). If you exceed the plan allowance, you can purchase additional usage as needed.
Answers about privacy, deployment, models, and delivery.
Hast is a privacy-first AI Native platform for enterprises. It connects internal data, systems, and workflows into governed AI agents and operational digital twins, delivered with FDE support.
Codex and Claude Code are excellent general-purpose tools. Hast focuses on the enterprise implementation layer: private deployment, systems integration, permission-aware workflows, ontology-backed context, and auditable operations.
Not necessarily. Hast works with models and agents your company already trusts, and adds the enterprise layer around them: context, permissions, workflows, integrations, and governance.
Yes. Hast supports private, VPC, and hybrid deployment patterns based on your requirements.
The ontology layer is a structured model of business objects and relationships, such as content, leads, courses, repositories, customers, tickets, owners, and workflows, so AI can reason over enterprise context reliably.
It is a live, AI-readable operational model that combines data, systems, relationships, workflows, status, risk, and decisions so teams can query, simulate, and act.
A production-grade workflow, connected sources, focused ontology map, governance controls, measurable outcomes, and an expansion roadmap.
Hast pairs the platform with forward-deployed engineers who work directly with your business and technical teams.
Yes. Hast supports existing model and agent stacks, including Hermes and private model deployments within governed enterprise controls.
Start with one workflow, one team, and clear success metrics, and we will help you go from pilot to production
