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ai workflow automation

AI workflow automation built and run end to end.

Gaper turns the workflows your team already documents into supervised production agents that run inside your systems. We map the process, build on the right model, connect your stack, and go live with evals, approvals, and an owner.

Book a free AI assessmentWhat is an AI agent?
Map the workflowBuild the supervised agentSandbox, verify, go live
gaper · agent runtime
$ gaper deploy agent --to production
✓ plan ……………… 4 steps
✓ retrieve …… 1,240 docs grounded
✓ tool ………… salesforce.update_record
✓ eval ………… 12/12 checks passed
● live · p95 1.2s · 0 errors
● in productionowned by your team
In one sentence

AI workflow automation is the practice of turning a repeatable business process into a supervised production agent that reads your inputs, reasons through exceptions, and takes action across your systems. Gaper builds it on OpenAI, Claude, or Gemini, deploys it in your cloud, and hands you the code, evals, and runbook.

ProductionNot another demo
Model-agnostic
In your cloudYour auth, your data
You own itCode, evals, runbook
Why this matters

Most automation work stalls between a working demo and a system that survives real data, real exceptions, and real users. Closing that gap, in production, is the only part that changes a number.

Production filter
  • Does it touch real systems?
  • Can the outcome be measured?
  • Where does human approval stay?
  • Who owns it after launch?
Free AI assessment

Book a free assessment. We will identify one high-leverage workflow, make the build-vs-buy call, and scope the smallest production release.

Map your first production agent
How we work

From strategy to production, owned by your team.

  1. 01

    Map the workflow

    We start from the documents, SOPs, portals, inboxes, and spreadsheets your team already uses, then turn the repeatable path into an agent workflow map.

  2. 02

    Build the supervised agent

    We build on OpenAI, Claude, Gemini, or the right model for the job, with evals, guardrails, citations, and human approval gates where risk matters.

  3. 03

    Connect the stack

    The agent gets the data layer, APIs, MCP tools, auth, and write-backs it needs to finish work inside your systems, not beside them.

  4. 04

    Sandbox, verify, go live

    We launch in a sandbox, verify every run, then move into supervised production with traces, rollback, and an owner.

What we build

Agents wired into the systems you already run.

Workflow mapping

We start from your SOPs, templates, inboxes, portals, and spreadsheets, then turn the repeatable path into an agent workflow map.

Agentic automation

Agents that reason through unstructured inputs and edge cases and decide the next step, where fixed-rule automation breaks.

Document and email processing

Read messy inputs, extract the fields, reconcile, and route the exceptions, running unattended at production scale.

System integration and write-backs

Wired into your CRM, ERP, ticketing, and warehouse via your APIs and MCP, so the agent finishes work inside your systems.

Evals and human gates

Automated evals and approval steps on signatures, submissions, and other consequential actions, with clean escalation.

Observability and tuning

Traces, cost, and outcome dashboards so you see every run, then continuous tuning as your process changes.

Beyond fixed rules: agents that handle exceptions

Rule-based automation breaks the moment reality gets messy. We build agents that read unstructured inputs, reason about the edge cases, and know when a step needs a human, so the workflow keeps running instead of stopping at the first surprise.

  • Reads documents, emails, and portals
  • Decides the next step, not just routes
  • Escalates cleanly when unsure
Control room
approval queue3 cases need human sign-off

Low confidence, policy exception, or protected data.

01Source checked02Risk scored03Human approved04Audit trail saved

Start from the metric, not the task

We do not automate for its own sake. Every engagement begins with the number you want to move, cycle time, cost per ticket, days to close, and we automate the workflow that moves it most. The agent ships with instrumentation so impact shows up as evidence.

  • Tie each agent to a target metric
  • Prioritize the highest-leverage path
  • Prove impact in a dashboard
Outcome tracker
measured lift, 90 days+38%▲ trending up
W1W2W3W4W5W6
+3.5xthroughput-42%cycle time100%traceable

Built into production, owned by you

We deploy where your data lives: your cloud, your auth, your controls. The agent inherits your security posture, and we hand over a clean, documented codebase with evals and a runbook so your team can run and extend it without us.

  • Runs in your environment with SSO and RBAC
  • Full audit trail and rollback
  • You own the code, evals, and runbook
Deploy target
OpenAIOpenAIClaudeClaudeGeminiGeminiSalesforceSalesforceSnowflakeSnowflakePostgresPostgres
SSORBACAudit logCloud
Model and stack agnostic
OpenAIClaudeGeminiLangChainMCPPythonTypeScriptPinecone
FAQ

Questions buyers ask us.

What does AI workflow automation from Gaper actually include?+
A full path from a documented workflow to a supervised production agent: discovery and workflow map, the data and connector layer, the agent built on the right model, automated evals, a sandbox run, and a human-gated go-live. You receive the code, evals, and runbook.
How is this different from RPA or a workflow tool?+
Rule-based automation follows fixed scripts and breaks on exceptions. Our agents reason about unstructured inputs and edge cases, take action across your systems, and escalate to a person when a step carries risk. We build and deploy the agent for you, wired into your specific stack.
Can you deploy inside our cloud, and which models do you use?+
Yes. For regulated workflows we deploy in your cloud with SSO, RBAC, PII redaction, and full audit logging, so data never leaves your boundary. We are model agnostic: OpenAI, Claude, Gemini, or open models, integrated via your APIs and MCP.
How long until an automation is live, and who owns it after?+
A first working build can land in as little as 24 hours for a scoped workflow; production timelines depend on integration and governance, typically weeks. You own the code and documentation, and we can hand it over or run it under an SLA, your call.
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Ready to deploy your first agent?

Book a free 30-minute assessment. We'll map the highest-leverage workflow and scope the smallest thing worth shipping, live in as little as 24 hours.

Build, deploy, runYour cloudYou own the code