A working agent in your sandbox
Not a slide deck. A running agent on real data by the end of week three, with its failure modes visible to everyone.
Task automation
Service
AI agents for the repetitive tasks your team avoids.
Multi-step AI agents that take over long, repetitive tasks: inbox triage, refunds, reporting and follow-up, vetted with evals and shipped with guardrails.
What it is
Task automation at Agnotiq means a multi-step AI agent that picks up a long, branching process your team keeps postponing, runs it end to end inside the tools you already use, and hands the exceptions back to a person. Every agent is vetted with an eval suite before it ships and deployed with guardrails and a kill-switch.
Most small and mid-sized teams don't have a tooling problem. They have a queue of repetitive work that never quite gets done: the inbox that needs sorting, the refund that needs three checks, the weekly report someone assembles by hand. Rules-based automation handles the deterministic parts. The rest needs judgment, and that is where an agent earns its keep.
We start from the score, not the story. Before the agent exists, we write the eval suite with your subject experts, so "done" has a definition. Then we build the agent in your sandbox, run it against real data and real edge cases, and ship it only once it clears the bar. About one in five prototypes never does, and that is the system working as designed.
What you get
Included in every engagement.
An eval suite your team owns
Hundreds of scored cases, run on every prompt change and every model swap, kept in your repo and your CI.
Guardrails, canaries and a kill-switch
Rollout starts small, observability is piped to the channels you already use, and every agent can be paused in one action.
Human approval where it matters
Low-risk work moves on its own. Higher-risk cases stay visible for a one-tap review in a dashboard or in Slack.
How it works
From discovery to production.
Map the loop
Two weeks sitting with your team to find the three repetitive loops where an agent pays for itself fastest.
Prototype on real data
A working agent in your sandbox by week three, run against the messy cases, not the demo cases.
Evaluate before shipping
Your experts score the eval suite. The agent ships when it clears the bar, not when the calendar says so.
Deploy and operate
Canary rollout, telemetry and kill-switches, then a quarter on call tuning prompts and swapping models.
The full five-phase rhythm is on the process page.
A good fit when...
- A recurring process with clear inputs, a known "good" outcome, and enough volume that the hours add up.
- Work that branches: sorting, drafting, checking, updating a record, deciding who handles the exception.
- Teams that want the agent in their own cloud and repo, with an off-switch they control.
Agents already doing this work.
Inbox automation
Email AI Agent
24/7Inbox triaged on arrival
SecondsTo a ready-to-send draft
100%Replies approved by you
View case study
Refund operations
Lumtry
92%Routine cases auto-handled
1-tapApprovals from dashboard or Slack
FullAudit trail on every decision
View case study
Analytics
Data Analyst Agent
< 5 minFrom CSV to full report
6+Chart types built automatically
100%Repeatable, consistent analysis
View case study
Questions we hear first.
Repetitive, multi-step work with a clear definition of done: inbox triage, refund handling, report assembly, follow-ups and record updates. If a person can explain how they decide, we can write an eval for it, and if we can write an eval, we can ship an agent against it.
Two weeks of discovery, then a working prototype in your sandbox by the end of week three. Production rollout follows once the eval bar is met, typically inside the four-week Sprint.
They go to a person. Every agent we ship routes low-confidence or high-risk cases to a human review step, in a dashboard or in Slack, with the evidence attached.
No. Agents connect to the email, ticketing, payment and data systems your team already runs. The work stays where it is; the agent moves it along.
More answers on the FAQ page.
More ways we put agents to work.
Agentic workflowsAgentic workflows that move work across the tools you already use.Real-time intelligenceAgents that read wikis, tickets, contracts, PDFs and live market data and return answers with citations and graded evidence your auditors can sign off on..Custom AI agent developmentCustom AI agents designed, built and shipped in your repository and cloud, with the eval suite, telemetry, model routing and runbook included from day one..AI strategy consultingOperator-led AI strategy.For operations leadersFor operations leaders, Agnotiq deploys AI agents that take over recurring coordination work across the systems the business already runs: routing, follow-up, approvals, status updates and reporting.For customer teamsFor customer support and success teams, Agnotiq builds agents that capture complete details at intake, classify and route every request by your rules, draft replies matched to the conversation, and escalate exceptions to a person.
Let's build
Have a workflow that deserves an agent?
Tell us what's eating your team's afternoons. We'll come back inside three days with a discovery plan, a price, and the names of the engineers we'd put on it.