Aelix Echo · Process Automation
Work that runs
while you're not watching.
End-to-end workflow, including the branches nobody documented. Audit-clean automation for healthcare, financial services, and manufacturing, with audit trails designed to support SOC 2 and HIPAA evidence.
Agentic AI · Process agents · Now live
From scripted bots to reasoning agents that handle the exceptions.
Traditional RPA breaks the moment the script meets reality. A field is empty, a counterparty is new, a payer's portal changes a label. Aelix Agents are the layer that picks up where the script ends. They reason over the exception, gather the missing context, propose the next step, and escalate when judgment is needed. The deterministic workflow engine is still the system of record. Agents become callable steps inside it.
Process Orchestrator Agent.
Reads an incoming case, decides which sub-workflow it belongs in (eligibility, coding, intake, reconciliation), and routes it. Cites the policy or rule that drove the decision.
Exception-Handling Agent.
Picks up cases that fall out of the deterministic flow. Gathers the missing fields, drafts the correction, and proposes a resubmission. Critical breaches block. Soft breaches escalate.
Handoff Coordinator Agent.
When an action needs a human, the agent prepares the case file: the inputs, the decision points, the agent's draft, and the rationale. The human picks up a worked case, not a blank one.
Continuous-Improvement Agent.
Watches recurring exception patterns and drafts proposed rule changes for the team. Drafts only. No rule ships through the agent. The detection engineer reviews and stages tests.
Trust architecture
Agents propose, the workflow engine acts.
Every irreversible step (submit a claim, post a payable, send a customer message) stays a dedicated, gateable tool. The agent never bypasses a deterministic gate.
Human-in-the-loop at every threshold.
Dollar caps, timely-filing deadlines, regulator-bound actions, customer-facing outbound: each routes through an explicit approval gate. The agent prepares. A person approves.
Audit-logged on every step.
Every agent decision, every tool call, every approval lands in the same tamper-evident log. The audit trail is non-forgeable.
Tenant-scoped and isolated.
The agent runs under the caller's role and tenant. Cross-tenant reads are impossible at the data layer. PHI, PII, and financial data stay inside the trust boundary.
Client work · Microsoft Power Platform
The delivery stack fits the client.
A customs import and export team.
Two platforms, one for import and one for export documentation. A chain of AI agents reads and checks every document, and people review only what is flagged.
Read the case studyA medical device manufacturer.
Supplier invoice processing automated on Microsoft Power Platform, with LLM-based field extraction in Power Apps AI Builder.
Read the case studyYour stack, not ours.
Power Apps and Power Automate for Microsoft-centred teams. Aelix Echo's own agent framework otherwise. The workflow, the gates, and the audit trail work the same way on either.
The thesis
An automation only works if a human can audit it, recover from it, and trust what it did when they weren't watching.
Most automation programs stall on the same thing: the work that runs fine in the demo falls over the moment it meets a real exception, a regulator, or a Monday morning. We build for the Monday.
What we automate
Workflow orchestration that survives the real edge cases.
We model the full process, the happy path and the wrong turns, then encode it as a versioned workflow. Every branch, retry, and timeout is a deliberate design choice, not a discovery in production.
Integration with the systems your business actually runs on.
ERPs, core banking, EHRs, claims systems, ticketing, mainframes. We connect to the systems already in place, and we treat their schemas, latency, and downtime as engineering constraints, not afterthoughts.
AI agents with intent, scope, and guardrails.
Agents handle the steps that benefit from judgment: classification, extraction, drafting, summarization, decisioning. Every call is scoped, logged, and reversible, so model behavior never quietly becomes business policy.
Human-in-the-loop, by design.
Confidence thresholds, exception queues, reviewer workflows, and time-bound handoffs. The operator stays in command for the calls that matter, and the system gets out of their way for the ones that don't.
Audit trails, evidence, and the boring parts that pass inspection.
Every action timestamped, every input preserved, every model decision explainable. Audit trails designed to support SOC 2 and HIPAA evidence, and the internal compliance team that's seen too many half-built workflows.
A glimpse of the work
Accounts payable · illustrative run
Workflow run trace · accounts payable
+ Agentic AI
Where rules end, the agent begins.
Workflows do the deterministic work fast. Agents take over for the one step that needs judgment, and hand back the moment they're done.
What you get
Mapped
Every branch, including the ones nobody documented
Gated
Irreversible steps wait for a person
Logged
Every action in a tamper-evident trail
Where it applies
Seven industries, the process that bottlenecks them, and what we automate.
How we work
A short discovery, a measured rollout, and a long, quiet operate.
Discover
We sit with operators, map the process, and find where time, money, and trust quietly leak today.
Map
Every system, hand-off, exception, and human checkpoint, sketched as a working process map before any automation runs.
Orchestrate
Workflow code, integrations, AI agents, and human queues, rolled out gradually and observed from day one.
Operate
Monitoring, exception triage, model recalibration, and the iteration that turns a launch into compounding savings.
A note from the practice
We don't build bots that hide what they did. Every action is auditable, recoverable, and explainable, because the moment one isn't, the operator stops trusting the system, and the trust is what kept the throughput.
The Aelix Echo automation practice
When the work needs to run without you watching, we're here.
45-minute working session · One real process, scoped live