AI Automation
Agentic automation for the operations that quietly eat your team's time — documents, email, data entry, approvals, follow-ups. We connect your tools, give AI agents narrow jobs with hard guardrails, and measure the result in hours returned per week.
What We Build
Invoices, contracts, claims, IDs, shipping docs — extracted, validated against your rules, and pushed into your systems. OCR plus language models plus human-in-the-loop review for the edge cases.
Agents that read shared inboxes, classify intent, draft responses in your tone, route exceptions to the right person, and never let a customer email sit for three days.
Deduplication, enrichment, activity logging, and follow-up sequences that actually fire. Your CRM becomes a system of record instead of a system of guilt.
Purchase approvals, onboarding checklists, compliance steps — modeled explicitly, executed by agents, escalated to humans exactly where your policy says so.
When off-the-shelf automation tools hit their ceiling, we build custom agents on your stack — with the queues, retries, idempotency, and monitoring of real backend systems.
Every automation ships with a counter: tasks handled, exceptions raised, hours returned. If we can't measure it, we don't call it a win.
Why Algogile
We don't deploy a general agent and hope. Each agent gets a tightly scoped job, explicit permissions, and an audit trail — the same discipline we apply to any production service.
ERP, CRM, helpdesk, spreadsheets, legacy databases — a decade of systems-integration work means we connect to what you actually run, not what a demo assumes.
Exception queues, review steps, and kill switches are designed in from day one. Automation should reduce risk, not concentrate it.
Questions, Answered
High-volume, rule-heavy, low-creativity work: document intake, email triage, data entry between systems, status chasing, and report assembly. We start with a process audit and rank candidates by hours saved versus implementation risk.
Every workflow has confidence thresholds and exception queues — uncertain cases route to a human reviewer with full context, and corrections feed back into the system. You define the risk tolerance per process.
No. We automate across the tools you already use via their APIs. Replacement is only on the table when a tool is genuinely the bottleneck — and that's your call, made with data.
A 30-day POC automates one real process end-to-end and reports the hours returned. From there, the roadmap writes itself.