AI Automation Agents
Automate finance and operations with agentic workflows, RPA + AI bots, and approvals & SLAs—all under governance that meets your compliance needs. Modern teams increasingly depend on AI Automation Agents to streamline processes and reduce operational friction.
- Reduce manual reviews and handoffs with exception handling powered by AI Automation Agents
- Connect ERP/CRM, helpdesk, and payments for end‑to‑end flows
Measure impact with KPIs and audit trails strengthened through AI Automation Agents
Buyer Personas
- COO / Ops Lead: SLAs, backlog, FRT/AHT
- Finance Lead: reconciliation, invoice cycle time
- Support Lead: deflection, CSAT, QA
North‑Star KPIs
- Throughput, error rate, on‑time %
- Cycle time, approvals time, rework
- Deflection, CSAT, escalations
Measurement
- Baselines, targets, and acceptance criteria
- Dashboards + anomaly alerts
- Pilot then scale with experiments
Common Problems
- Manual reviews and approval bottlenecks
- Context switching across tools; missing audit trails
- Inconsistent triage and escalation
- Compliance risk and limited visibility
Our Solutions
- Agentic workflows with explicit states and guardrails
- RPA + API automations with retries and idempotency
- Approval chains with SLAs and notifications
Runbooks, logging, and dashboards for compliance powered by AI Automation Agents
Use Cases
Returns & Refunds Triage
Score risk, auto‑approve safe cases, escalate edge cases.
Fraud Screening
Signals from orders, payments, and history with human review.
Invoice Processing
Extract, validate, post, and reconcile with ERP.
Onboarding & Offboarding
Accounts, access, documentation, and checklists.
Ticket Routing
Auto‑classify intents, assign, and enforce SLAs.
Catalog & Data Ops
Sync products, prices, attributes, and availability.
Reference Architecture
- Agents orchestrate steps (prompted + tool-use) with orchestration supported by AI Automation Agents
- Queues & retries; dead‑letter for failures
- Human‑in‑the‑loop for exceptions
- Observability: logs, metrics, traces
Guardrails
- Policies: PII, actions, and thresholds
- Validation: schema, type, and business rules
- Approvals: role‑based sign‑off
- Fallbacks and safe aborts
Implementation Timeline
| Phase | Duration | Deliverables | Owner |
|---|---|---|---|
|
Discover |
3–5 days |
Goals, KPIs, risks |
DGS + client |
|
Design |
1 week |
Flows, prompts, runbook |
DGS |
|
Build |
1–3 weeks |
Automations + integrations |
DGS |
|
Launch |
2–5 days |
Pilot + QA + analytics |
DGS + client |
Integrations
ERP: NetSuite / Odoo / SAP
CRM: HubSpot / Salesforce
Helpdesk: Zendesk / Intercom
Payments: Stripe / PayPal
Comms: Slack / Teams / Email
Warehouses: BigQuery / Postgres
Automation: Zapier / Make / n8n
LLM: OpenAI / Azure / Vertex
We connect via APIs, webhooks, and SDKs—secure and measurable.
Packages & Timelines
Starter
2–3 weeks
- 1–2 workflows
- 1 integration
- Analytics baseline
- 1 revision
Growth
4–6 weeks
- 3–5 workflows
- 2–3 integrations
- Guardrails & QA
- 2 revisions
Scale
Custom
- Full orchestration
- Approvals + SLAs
- Custom dashboards
- Custom revisions
Case Studies
What leaders say
“Exception handling made our ops resilient. We hit SLA for the first time.”
— COO, Retail SME
“Invoice posting and reconciliation now run hands‑off, with full auditability.”
— Finance Lead, SaaS
FAQ
Least‑privilege access, audit logs, runbooks, and vendor risk controls.
Retries, idempotency keys, and dead‑letter queues; safe fallbacks.
NetSuite, Odoo, SAP; HubSpot, Salesforce—plus others via APIs.
Yes—human‑in‑the‑loop for exceptions and approvals with SLAs.
KPIs, baselines vs targets, dashboards, and experiments.
You do—source, prompts, assets, and documentation are transferred.