The intelligent ops layer
The operating model for enterprise AI workflows.
BergFlow and BergAuto keep work moving through one measurable loop, with human judgment where it matters.
- 01IntakeEmail, documents, voice, ticketsBergFlow
- 02StructureClassify and extractBergAuto
- 03RouteOwner, priority, SLABergFlow
- 04AI assistDraft, score, actBergAuto
- 05Human reviewExceptions and approvalsNamed person
- 06LogVersion and evidenceBergFlow
- 07MeasureSLA, QA, outcomeBergFlow
- LoopCorrections feed backRules and thresholds update
- One loop
Seven steps from intake to a measured outcome.
- One boundary
Automate the repeatable. Review the uncertain.
- One record
Every action and decision logged in BergFlow.
Operating loop
Intake, structure, route, assist, review, log, measure.
The same seven steps run under every workflow, whether the item is a refund, an invoice or a robot take. Platform ownership never changes: BergFlow holds the record, BergAuto does the scored work, people decide.
- 01
Intake
Work arrives from the channels it already uses: email, documents, voice, forms and tickets. Each item gets a governed record in BergFlow the moment it lands.
- 02
Structure
BergAuto classifies the item and extracts the fields a decision needs, with a confidence score on every output.
- 03
Route
BergFlow assigns an owner, a priority and an SLA timer, so no item waits in a shared inbox without a name on it.
- 04
AI assist
Repeatable steps run on BergAuto: drafting, matching, enrichment, system updates. Anything below the agreed threshold waits for a person.
- 05
Human review
Exceptions, regulated calls and high-value decisions go to a named reviewer with the evidence attached.
- 06
Log and measure
The decision is versioned with its evidence, and SLA adherence, QA results and the outcome are reported every week. Corrections feed back into the rules.
Sample lifecycle
TKT-4429: refund escalation.
One ticket, before and after the layer. The work is the same; ownership, evidence and timing are not.
Before the layer
Handled by hand, decided in a chat thread
- 09:02The ticket lands in a shared inbox with no owner.
- 15:10An agent picks it up and checks the refund policy by hand.
- 15:40The amount is over the agent’s limit, so it is escalated in a chat thread.
- Next dayA manager approves it. Nothing records who decided, or why.
With the intelligent ops layer
Governed end to end, with the evidence attached
- 09:02Intake: BergAuto classifies the intent as a refund escalation at 0.96 confidence.
- 09:03Structure: the order, amount and policy clause are attached to the record.
- 09:03Route: the amount is above the agreed threshold, so BergFlow routes it to a team lead on a 4-hour SLA.
- 10:15Review: the team lead approves with a note, and the decision is versioned.
- 10:16Log and measure: the reply goes out, QA samples it, the SLA is met.
Illustrative timeline. Times, thresholds and owners are set per workflow at scoping.
Automation boundary
What gets automated, and what gets reviewed.
The boundary is agreed before go-live and set from shadow-run evidence. Every automated step is still scored and logged, so the line can move as trust is earned.
Automate
Repeatable work with a known rule
- Repeatable steps
- Known rules
- Clear confidence thresholds
Review
Judgment that needs an owner
- Exceptions
- Regulated calls
- High-value decisions
- Uncertain outcomes
Illustrative readouts from a sample refund workflow, not a client result. Your boundary is set per workflow.
Governance
Governance is built into the workflow, not added later.
Six controls ship with every workflow on the layer. None of them depend on someone remembering to switch them on.
- 01
Role-based access
People see and act only on the queues, records and actions their role allows, project by project.
- 02
Audit logs
Every automated and human action is written to BergFlow with the time, the actor and the evidence.
- 03
QA sampling
Automated and human work are both sampled against the agreed standard, batch by batch.
- 04
Exception paths
Every exception type has a named owner, a route and an SLA before the workflow goes live.
- 05
Reporting
SLA adherence, QA pass rate and exception rate are reported weekly against the agreed targets.
- 06
Rules framework
Thresholds, policies and approval limits are versioned rules; every change records who made it and why.
Function fit
Where the loop runs first.
Six functions where volume, risk and quality matter most. Pick one to see its scope and two workflows from the use-case library, with example figures.
Customer operations
Ticket triage, refunds, escalations, QA sampling and sensitive replies, with people on the exceptions.
- Ticket triage + routing75% faster routing
- Call/chat summarisation + dispositionWrap time -45%
Sales & marketing
Lead enrichment, routing, campaign QA, CRM hygiene and handoff control.
- Lead enrichment + validation60% time saved
- ABM campaign QAQA defects -54%
Finance & accounting
Invoice matching, reconciliation, approvals, vendor checks and audit support.
- Payment reconciliation + dispute resolutionUnmatched items -40%
- Invoice intake + exception triageCycle time -52%
People & HR
Onboarding packets, policy checks and people-data hygiene.
- Employee onboarding workflow ownership40% TAT cut
- Document verificationVerification -50%
Legal & compliance
Contract review support, obligation tracking and audit-ready evidence trails.
- Clause extraction + risk flagging62% faster review
- Evidence pack preparationPack prep -55%
IT operations
Access reviews, internal ticket triage and asset data kept clean at scale.
- Incident triage + routingMTTR -45%
- Access request approvalsApproval TAT -50%
Metrics are the outcome tracked for each workflow in the BergLabs use-case library; pilot targets are agreed per engagement.
BergAuto capability benchmark
What the automation layer does that other approaches leave out.
Native means built in and operated by BergLabs. Partial means possible with extra build. Limited means not designed for it.
| Capability | BergAuto | Open-source orchestration | In-house build | Model builder |
|---|---|---|---|---|
| Visual canvasOne canvas for intake, AI steps, conditions, waits and outputs | Native | Partial | Limited | Limited |
| Batch executionThousands of items run through the same workflow | Native | Native | Partial | Partial |
| Multi-format intakeEmail, documents, voice, images and structured data | Native | Partial | Partial | Partial |
| One master workflowOne governed definition per process, versioned | Native | Partial | Partial | Limited |
| Human wait statesRuns pause for a named reviewer and resume | Native | Limited | Partial | Limited |
| Confidence-gated routingEvery step scored and routed by band | Native | Limited | Partial | Limited |
| Run ledgerInputs, scores and decisions recorded per run | Native | Partial | Partial | Limited |
| Operating ownershipA named team runs the workflow to an SLA | Native | Limited | Partial | Limited |
Evidence note: BergLabs assessment of each category as typically deployed, October 2026. Individual products vary; ask us for the criteria behind any cell.
Questions
Questions about the intelligent ops layer
How the loop, the boundary and the record work together.
The model
What is the intelligent ops layer?
It is BergLabs’ operating model for enterprise AI workflows. BergFlow holds the record, routing and audit trail; BergAuto runs the repeatable steps with a confidence score; named people review what automation should not decide alone.
Does it replace our existing systems?
No. The layer connects to the CRM, ERP, ticketing and document systems already in place, so there is no rip and replace. Records stay where they are, and BergFlow keeps the governed copy, the decision history and the evidence.
How do you decide what gets automated?
A step is automated when it repeats, follows a known rule and clears an agreed confidence threshold. Exceptions, regulated calls, high-value decisions and uncertain outcomes go to a named reviewer with the evidence attached.
Running it
How is quality measured?
Every workflow reports SLA adherence, QA pass rate and exception rate weekly against targets agreed at scoping. QA sampling covers automated and human work alike.
How do we start?
With one workflow and a 4-week pilot: audit the flow, build the rules, run a live queue and prove the result against a measured baseline.
Bring one workflow into production discipline.
Tell us the queue and the outcome you need. We map it onto the loop and return a pilot plan within one business day.