Data Readiness
Prepare company data for reliable AI agents
Product overview
A managed AI agent system for business work.
TactasAI combines data readiness, system design, workspace isolation, company knowledge, research-grade context, supervised AI agents, connected workflows, guardrails, and ongoing improvement so repeated business tasks become useful outputs and controlled action.
Tactas product map
Product Overview
Foundation
Prepare data and context so agents can retrieve, reason, and work from the right business material.
Execution
Define how agents behave, where they act, and how work moves through business systems with guardrails.
Task Review
Pick one workflow with clear value, context, output, and ownership.
Data Preparation
Make company data usable for agent retrieval, reasoning, and action.
System Design
Fit agent behavior to your workflows, rules, tools, and operating model.
Workspace Isolation
Separate data, tools, context, permissions, and agent behavior by workflow inside one business.
Product clusters
Two clusters, one managed system.
The product is not a chatbot or connector list. It is the operating layer that turns trusted context into supervised work.
Foundation
Prepare data and context so agents can retrieve, reason, and work from the right business material.
Execution
Define how agents behave, where they act, and how work moves through business systems with guardrails.
Capabilities
The pieces that make agents usable in real operations.
Task Review
Pick one workflow with clear value, context, output, and ownership.
Data Preparation
Make company data usable for agent retrieval, reasoning, and action.
System Design
Fit agent behavior to your workflows, rules, tools, and operating model.
Workspace Isolation
Separate data, tools, context, permissions, and agent behavior by workflow inside one business.
Deep Research
Use company knowledge and approved sources to prepare cited briefs for harder business questions.
Connectors & Actions
Use existing apps as inputs, destinations, and controlled action paths.
Workflow Actions
Move approved outputs into tasks, records, messages, and reports.
Guardrails
Define approvals, escalation rules, limits, and review points before launch.
Monitoring
Track output quality, usage patterns, exceptions, and improvement opportunities.
Knowledge Quality
Tune retrieval, citations, source freshness, and answer usefulness.
Managed Improvement
Improve prompts, context, actions, and workflow rules as real work changes.
Launch model
Start with one task. Expand after it works.
01
Review
Choose one repeated business task and define what useful output should look like.
02
Connect
Bring in the documents, records, messages, and tools the agent needs.
03
Launch
Ship a supervised agent with approvals, outputs, and action paths.
04
Improve
Tune the system with real usage, edge cases, and changing business context.
Product review
Define the first AI agent your business should trust in production.
Share one repeated task, the sources it depends on, and the tools where work should move next.