From disconnected systemsto agents runningreal operational work.
Four steps, in order, for a reason. Connect the stack, build the skills, deploy the agents, train your team to keep shipping without us.
Agents got capable. Most companies didn't.
Frontier models are now capable of real operational work — not just chat, not just code. They can run approvals, reconcile invoices, draft RFPs, maintain pipelines, and keep records in sync across systems.
The blocker isn't the models. It's that most companies don't have a mature digital transformation strategy — let alone integrated systems. So even the most capable agent has nowhere to act. No connectors, no rules, no audit trail, no place to land.
Specialty Tokens fills that gap. We connect the systems, build the skills, deploy the agents, and train your team to keep shipping — in that order, for a reason.
Each step unlocks the next. Skip one and the rest doesn't hold.
Written in the order we run them. Every engagement moves through all four — the scope changes, the sequence doesn't.
- Connect
Wire up the systems agents can't reach on their own.
The hard-to-reach enterprise stack — BMD, DATEV, Navision, Exact, weclapp, on-prem ERPs and legacy cores — gets custom connectors. Your mainstream tools (Salesforce, HubSpot, Slack, Google, Notion, Jira) get integrated alongside them.
One permission model, one audit trail, one place agents can act from. SSO, roles, and EU residency wired in from day one.
- Build skills
Small applications agents actually run.
Once systems are connected, we package the work your team does every day into skills — compact, versioned applications agents call to perform real automations. Approvals, reconciliation, research, onboarding, reporting.
One skill per operational workflow — scoped, testable, owned. Each runs against your connected stack, under your rules, with every version and author recorded.
- Deploy
Agents from any AI tool, or running on their own.
Your team calls skills from the AI tools they already open — ChatGPT, Claude, Gemini, Copilot. No new surface to learn. The work happens where the work already happens.
In parallel, agents run in the cloud: kicked off by a person, a schedule, an incoming event, or another agent. Same skills, same rules, same audit. Every run logged — who called it, what it touched, what changed.
- Educate
Your team keeps building after we leave.
Workshops, hands-on pairing, and internal playbooks — so skill authoring, connector maintenance, and agent design stop being things you outsource.
By the time we roll off, your team is shipping new skills without us. No lock-in, no dependency, no quiet renewal clause. A roadmap your team extends on its own cadence.
A company-owned AI layer. Not a vendor you depend on.
Four things stay behind when we roll off. They belong to you, run on your permissions, and keep compounding without us in the room.
- Connectors
- Owned by you. Reusable across every AI tool your team adopts — not rented from a platform.
- Skills
- Your operations encoded as runnable applications. Versioned, audited, and attributed to an author.
- Agents
- Running locally in assistants, on schedules, on triggers, or chained from other agents.
- Capability
- A team that authors skills, maintains connectors, and ships the next wave without us.
Start
See the process on your real systems.
Talk to the team30 minutes. We'll scope connectors, the first skills, and a realistic rollout plan before you commit to anything.