The AI workflow operating system for modern companies
ProDexter connects your tools and company context, routes every task to the right model, agent or person, and keeps each action governed.
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Unified company context
Your apps, threads, tickets and docs in one permission-aware context layer.
AI and human orchestration
Each task goes to the model, agent or teammate best placed to do it.
Enterprise governance
Approvals, policies, permissions and a full audit trail on every action.
Connects to the tools you already use
- Google Workspace
- Slack
- Jira
- Linear
- Notion
- GitHub
- Salesforce
- HubSpot
- Zoho
Three problems with today's workflow software
Fragmented company context
Knowledge is spread across tools, chat threads and repositories, so every task starts by hunting for context.
Manual coordination
Teams lose hours finding information, repeating context, chasing approvals and updating systems by hand.
Rigid automation
Rule-based integrations break on exceptions and cannot plan when work does not follow a straight line.
AI adoption is high. Business impact is still limited.
88%
of organizations use AI in at least one business function.
62%
of organizations are experimenting with or scaling AI agents.
65%
of organizations have not started scaling AI across the enterprise.
39%
of organizations report any enterprise-level EBIT impact from AI.
The missing layer is not another model. It is shared context, redesigned workflows, human validation and governed execution.
From objective to outcome
Connect
Link your apps with native connectors.
Context graph
Build a living map of company knowledge.
Index
Find relevant, permission-aware context.
Plan
Break objectives into tasks and dependencies.
Route
Assign the right model, agent or person.
Approve
Apply policies, permissions and review.
Execute
Carry out approved actions across your tools.
Learn
Store outcomes as reusable workflow memory.
Every workflow starts with your company context
Shared context that any approved model, agent or teammate can reuse. No more repeating yourself.
Models change. Your structured context and workflow memory stay with you.
Permission-aware, source-grounded, always up to date.
People and structure
- People
- Teams
- Roles
- Projects
Work items
- Conversations
- Tickets
- Repositories
- Documents
Systems and customers
- Applications
- Customers
Decisions and outcomes
- Policies
- Permissions
- Decisions
- Approvals
- Workflows
- Outcomes
Specialized agents, under human control
Eight specialized agents work from one shared company context. Each handles its own part of the work.
Planner
Plans the work.
Context
Finds the context a task needs.
Research
Researches.
Operator
Carries out approved actions.
Writer
Writes content.
Quality
Checks quality.
Governance
Applies governance.
Escalation
Escalates to an authorized person.
High-risk or uncertain actions go to an authorized person before anything runs.
Models generate. ProDexter orchestrates.
Company context graph
A permission-aware, source-grounded map of your people, work and decisions.
Native app connectors
Connect the tools your team already works in with native app connectors.
AI and human task routing
Each task goes to the right model, agent or employee.
Policy and task-aware model routing
Routing follows your policies and what each task needs.
Governed execution and approvals
Actions run inside risk tiers, with configurable approvals.
Reusable workflow memory
Outcomes are stored and reused by future workflows.
| Capability | Without ProDexter | ProDexter |
|---|---|---|
| Model selection | Manual selection per task | Routed per task to the right model |
| Human task routing | Manual sorting | Each task goes to the right agent or employee |
| Shared company context | Siloed in individual tools | One permission-aware context graph |
| Cross-agent context reuse | Repeated for each agent | Any approved model, agent or teammate reuses it |
| Context caching and optimization | Pasted in by hand | Only relevant context is selected and compressed |
| Human approvals | Handled separately | Risk-tiered approvals built in |
| Cross-tool execution | One tool at a time | Approved actions run across your tools |
| Workflow memory | Lost between tasks | Outcomes stored as reusable workflow memory |
Autonomy where it saves time. Control where it matters.
Low risk
Runs automatically.
Medium risk
Goes to a review queue.
High risk
Needs explicit approval.
External or irreversible
Blocked by default.
Governance controls
- Role-based access
- Audit logs
- Policy enforcement
- Tenant data isolation
- SSO/SAML
- Reversible actions
- Configurable single or multi-step approvals
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Estimate your savings
Every team's usage is different, so we don't quote a savings number. Put in your own figures and see the estimate.
The starting values are an example scenario. Change them to match your own.
Your team time
How many people spend part of their week on coordination.
Finding information, repeating context, chasing approvals, updating tools.
The fully loaded cost of one hour of their time.
Your AI spend
What you pay your AI provider in a typical month.
How much of what you send today is not needed for the answer. ProDexter's context selection and compression target this.
The share of your steps that do not need your most capable model.
What the lower-cost model charges compared with the model you use now.
Plans and prices come from the Pricing plans entries. The plan cost is subtracted from the savings.
Estimated monthly savings (net)
Estimated yearly savings (net)
- From sending less context
- From smarter model routing
- Hours freed per month
- Value of that time
- Minus plan
Estimate only, based on the values you enter. Real results depend on your workflows, models and provider pricing. With BYOK, model usage is billed by your AI provider. Time value estimates staff time, not a cash saving.
Built for product and engineering teams
How teams can use ProDexter on the workflows they already run.
Product launch orchestration
Product launches break at the coordination layer. Engineering tracks work in Jira, marketing plans campaigns in Notion, sales enablement lives in Google Docs, and status updates scatter across Slack. The...
Read use case Product launch orchestrationIncident coordination
When a P1 incident fires, responders waste critical minutes hunting for the right on-call person, digging through monitoring dashboards, Slack threads, recent deploys, and runbooks scattered across multiple tools. Coordination...
Read use case Incident coordinationBug triage
Bug reports arrive from support tickets, Slack threads, GitHub issues, and project trackers with no consistent format or priority. Engineers waste hours reading duplicates, guessing severity, hunting for related code...
Read use case Bug triageCustomer escalation management
When a customer escalates, support teams scramble across CRM records, Slack threads, past tickets, and engineering backlogs to piece together what happened. Severity gets misjudged, routing is slow, and SLA...
Read use case Customer escalation managementWhat we're building
Our roadmap is public. Priorities can change as we learn from customers.
Now
Native connectors for Slack, Jira, Notion and GitHub
Connect the tools where product and engineering work already happens.
Company context graph
A permission-aware map of people, projects, tickets, docs and decisions that every agent can reuse.
Planning and task routing
Break an objective into tasks and send each one to the right model, agent or teammate.
Risk-based human approvals
Low-risk actions run on their own. Higher-risk actions wait for an authorized person.
Next
Ready-made engineering workflows
Product launch orchestration, incident coordination, bug triage and customer escalation.
Governance controls
Role-based access, audit logs, policy enforcement and SSO/SAML for growing teams.
Reusable workflow memory
Store the outcome of every run so the next one starts with what your team already learned.
Slack App Directory and GitHub Marketplace apps
Install ProDexter from the places your team already finds tools.
Later
Broader connector library
More native connectors, including Linear and your internal systems.
Workflow-level optimization
Caching and policy-aware model routing across agents to keep AI usage efficient.
Security and compliance program
Independent security review and formal compliance work. Certifications are announced only once achieved.
See ProDexter on your own workflows
A 30 minute walkthrough with your use case, your apps, your questions.