Automate complex internal workflows with controlled AI agents.
Hexoia designs and ships AI systems that read messy inputs, use approved tools, and execute multi-step work inside clear operational boundaries.
Traditional automation breaks when the workflow stops being predictable.
Most operational bottlenecks are not caused by a lack of software. They come from work that sits between systems, requires interpretation, depends on incomplete rules, or needs someone to decide what happens next.
Controlled AI execution for the workflows rules cannot handle.
Hexoia builds agentic systems for workflows that require reasoning, tool use, and structured execution. The goal is not to add AI theater to existing operations. The goal is to give capable AI agents enough autonomy to complete useful work while keeping them inside explicit boundaries.
These systems are designed around sandboxed environments, approved tools, internal APIs, review paths, and clear operational control. That makes it possible to automate classes of work that were previously too ambiguous for traditional automation and too risky for uncontrolled AI access.
Examples of workflows that fit this model.
Hexoia is a strong fit when the work depends on internal systems, messy inputs, and repeated human coordination.
Technical credibility matters when AI is connected to real business systems.
Hexoia is led by Allan Tatter, a full-stack software architect with 18+ years in tech and 100+ projects delivered. The company’s edge is not generic consulting. It is the ability to combine systems architecture, internal integrations, sandbox design, and modern AI tooling into something operationally safe and commercially useful.
The strongest trust signals come from deep technical delivery experience, daily hands-on work with AI systems, and established credibility with complex organizations including Äripäev and Postimees Grupp.
Trusted by technical leaders across industries.
Allan's technical leadership has had an instrumental impact to our products. His deep understanding of complex systems and ability to deliver elegant solutions has significantly impacted our platform's development.
Kevin Valdek/CTO, High MobilityIt has been a pleasure working with Allan. His strategic thinking and technical expertise have helped us navigate complex challenges. He is first on my call list when I need help with AI-related projects.
Toomas Jõgi/CTO, ÄripäevSome people get it, how to iterate fast at startup speed. Allan is one of them.
Kaarel Holm/CEO, MeetFrankWhen you put Allan and his skills into an Excel sheet, doing business with him simply makes sense. More importantly, our core values align, and that's what I appreciate most.
Kaur Esnar/CEO, RingitWhen working with Allan, it is great to see that he focused on solving the business objectives rather than just following the spec.
Tanel Voorel/Product Manager, PostimeesStart with one high-value workflow.
The first step is a workflow audit. This is a structured discovery engagement designed to identify one strong automation candidate, map the relevant systems and safety boundaries, and define what a viable pilot should look like.
This keeps the first engagement concrete and low-risk. It is not an open-ended consulting conversation.
Apply for a Workflow AuditFrequently asked questions.
What makes a workflow a good candidate for a first pilot?
The best first pilots usually involve repeated manual work, multiple systems, fuzzy rules, and messy inputs. There should also be clear business value if execution becomes faster, more consistent, or less dependent on repeated coordination.
Do we need mature internal APIs before this can work?
No, but existing APIs and structured data help. Part of the workflow audit is understanding what interfaces already exist and where wrappers, internal tools, or constrained integrations are needed.
Can AI agents take actions directly in our systems?
Yes, but only inside defined operational boundaries. A workflow can be designed for read-only research, draft-first output, approval before sensitive actions, or direct execution for lower-risk tasks.
How do you handle private or sensitive internal data?
The systems are designed around explicit permissions, approved tools, bounded execution environments, and review paths. The goal is controlled AI access to a specific workflow, not broad unrestricted access to internal systems.
Who is this usually for inside a company?
The strongest fit is usually with CTOs, engineering leaders, operations leaders, product teams, or digital transformation leads. In practice, it works best in organizations that already have meaningful internal systems and workflow complexity.
Why start with a Workflow Audit instead of jumping straight into implementation?
The audit is the low-risk first step. It identifies one strong workflow candidate, maps the relevant systems and safety boundaries, and defines whether a pilot is worth building before anyone commits to implementation.
Find the workflow that should be your first controlled AI pilot.
Start with one high-value process where manual coordination is slowing the business down.