David Acremann
Co-founder · Director, Professional Services
Leads the forward deployed engineers who wire AI employees into your real systems and stay with you until go-live.
// AI employees · hosted in Europe
TaskFactory gives your organisation AI employees that do real work, ask before they act, and keep a record of every run. You set them up by configuration. The runtime already exists.
// Platform
A custom agent is usually a large bespoke project. On TaskFactory every part of it is a setting on a runtime that already exists, so you start small and change one part at a time.
Start from a template and describe the job in plain words.
Pick the model per task: OpenAI, Anthropic, Mistral, Gemini, OVHcloud or Scaleway, on your own models or on our private models.
Your documents and memory, searched when the job needs them.
MCP servers and any API, connected without code, OAuth included.
Workspace rules teams can tighten but never loosen, plus approvals.
Email, Slack, schedules, webhooks, voice, or a chat on your website.
// Features
Demos are easy. These are the parts that let an AI employee run every day, inside an organisation that answers to someone.
Call an employee and hear it answer, in the language you pick. Approve an action by voice.
One script puts an employee on your site or in your app, for visitors or signed-in users.
Questions and approvals reach Teams, Slack, Telegram, Discord, email or a webhook.
Reach your employees and workflows from Claude, ChatGPT or Le Chat.
See the exact action in plain rows, change any field, then approve or refuse with a reason.
When an AI reconfigures an employee, the change waits as a diff until a person applies it.
Halt every employee and workflow in the workspace at once while you look into it.
Decide which employees may pass work to which, and how long a chain may get.
Real requests are replayed against a new prompt, tool or model and graded pass, partial or fail.
A candidate model runs on the test set and is promoted only if it clears the bar you set.
Runs are analysed into findings, with evidence, that tell you what to fix first.
The dashboard counts outcomes a person accepted, next to what they cost.
Limits per workspace, employee or user, per run, day or month, with a warning first.
Paid tools are priced per run, not just model tokens.
A failed run picks up where it stopped, without asking for the same approval twice.
Send each run to Langfuse, Braintrust, Arize Phoenix or any OpenTelemetry tool.
// On the record
Prompts, tool calls, approvals and cost, step by step. When something goes wrong you follow what happened instead of guessing, and the result comes back as a table, a diff, a map or a chart rather than a wall of text.
// Workflows
Some work should run the same way every time. Workflows do that: signed webhooks, schedules, traffic caps, export and import. A workflow can call an AI employee for the step that needs reading or writing, and an employee can start a workflow.
// Your model, your key
Your API key lives in your workspace and your employees call the provider you chose, with no markup on tokens. Pick a model per task, and keep it in Europe when you need to.
// Use cases
What organisations put AI employees on first. Yours is probably close to one of these.
Lead qualification, quotes, RFP answers, meeting preparation and follow-up.
Competitive and technology watch, campaign drafts, social content, visuals.
Customer support, back-office questions in plain language, incident reports.
Expense and mail sorting, payment chasing, regulatory watch, clause review.
Job ads, CV screening, interview summaries, onboarding help.
Supplier quote comparison, price and raw-material watch, specifications.
Audit preparation, report drafting, diagnostic assistants.
Internal support, documentation, code review, questions over your systems.
Course creation and upkeep, diagrams, training videos, virtual coaches.
// How we work
No twelve-month programme. Something works within weeks, or we tell you it doesn't.
We map your workflows, systems and data, then pick the two or three tasks where an AI employee pays for itself first.
One task, wired into your real systems, tested before go-live, with a person approving what leaves.
More employees, more integrations, and your team trained to run them. We are meant to become optional.
// Founders
TaskFactory is not a product we resell. We wrote it, we operate it, and we know exactly where its edges are.
Co-founder · Director, Professional Services
Leads the forward deployed engineers who wire AI employees into your real systems and stay with you until go-live.
Co-founder · Sales Director
Leads business development. Your first contact to find the tasks where an AI employee pays for itself.
Co-founder · CTO
15+ years building and leading engineering teams across startups, scale-ups and enterprises. Has designed several software platforms and taken them into production, from architecture to operations.
// Contact
A short call is usually enough to tell whether you have an AI employee use case, an IT problem, or neither. We will say so either way.
Or write to contact@taskfactory.eu