AI Automation

AI Workflow Automation,
That Actually Runs.

AI agents and intelligent workflow automation for back-office, operations, support, and revenue teams.

We replace manual reconciliation, copy-paste data entry, ticket triage, and report stitching with reliable, monitored agents that integrate with the systems you already use.

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What you get when you work with us

Working AI agents
Production agents that read your tickets, documents, emails, or events and take action — written with explicit tool schemas, retry logic, and human-in-the-loop approval where the stakes call for it.
Workflow integrations
Connectors to Salesforce, HubSpot, Zendesk, Intercom, Slack, Gmail, Notion, BigQuery, Postgres, S3 — wherever the work actually happens. We do not ask your team to switch tools to make automation work.
Observability and guardrails
Every agent action is logged, every cost is attributed, every failure is retried with backoff. You see exactly what the agent did, what it cost, and what it skipped — not a black box.
Measurable hours-saved baseline
We instrument the workflow before automating it, so the ROI conversation is grounded in actual hours saved per week — not a vendor-supplied case study from a different industry.

Products in this practice

Who this is for

SaaS / B2B Software
Professional Services
Financial Services
E-commerce
Healthcare Operations
Legal & Compliance
Customer Support

Common questions

How is this different from RPA tools like UiPath or Zapier?

Traditional RPA records keystrokes and breaks the moment a UI changes. Zapier-style flows handle simple if-this-then-that triggers. AI automation handles the messy middle: reading an unstructured email, deciding which of 12 ticket categories it belongs to, drafting a context-aware reply, and only escalating the cases that need a human. We use Zapier and similar tools as glue when they fit, but the intelligence layer is custom.

What kinds of workflows are good automation candidates?

High-volume, rule-following work that still needs judgment: ticket triage and routing, invoice and contract intake, sales lead qualification, KYC document review, expense report categorization, internal report stitching from multiple data sources, and onboarding email sequences. The pattern: high frequency, costly to outsource, painful to scale linearly.

Will the AI hallucinate or make up data?

Hallucination is a design problem, not a model problem. We design agents with explicit tool schemas (the model can only call defined functions, with typed inputs and outputs), retrieval-grounded context (it cites the source document for every claim), and confidence thresholds (low-confidence outputs go to a human queue). For high-stakes workflows, we add eval harnesses that catch drift before it reaches production.

What does an AI Automation Audit cover?

A working session where we map your team's actual hours-per-week against specific repetitive workflows, then score each workflow for automation feasibility (data structure, decision complexity, integration surface, risk profile). The output is a ranked backlog with rough effort estimates — so you can decide which one to build first based on real ROI, not a vendor pitch.

Ready to scope a build?

A 30-minute discovery call gets you a problem framing, a reference architecture sketch, and a realistic timeline. No commitment.

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