Book a Flow Audit
Flow audit — on-site, fixed scope

We embed in your operations
and engineer AI into the flow.

Throughput Labs is a consulting firm that walks into your business, instruments how work actually moves — not how the documentation says it moves — and then integrates artificial intelligence precisely where your throughput is constrained.

Request a flow audit See engineering case studies

ERP · CRM · MES · WMS · CMMS · EHR · accounting · ticketing · logistics · e-commerce

flow-audit · order_to_cash.json
# Excerpt from a client flow-discovery report { "process": "order_to_cash", "discovered_activities": 17, "event_log_source": "erp.audit_trail + imap", "median_lead_time_h": 62.4, "value_added_time_h": 3.1, "flow_efficiency": 0.05, "primary_constraint": { "activity": "manual_exception_review", "avg_queue_time_h": 41.8, "monthly_volume": 4210, "rework_rate": 0.23 }, "ai_levers": [ "schema_constrained_extraction", "three_way_match_automation", "confidence_gated_escalation" ], "modelled_recovery_h_per_month": 1180 }
Phase 1
an on-site flow audit producing a quantified map and an ROI-ranked plan
0
from working prototype on your real data to supervised production rollout
3–5
activities usually carry the gain — never the whole process
Zero
forced platform migrations: we integrate with your systems of record
The diagnosis

It is almost never a software problem.
It is a flow problem.

Most organizations already own the tools. There is an ERP, a CRM, a warehouse system, shared mailboxes, spreadsheets, a ticket queue. Work still moves slowly, because it has to cross human interfaces: someone reads an email, retypes a value into another screen, checks a discrepancy, waits for an approval, chases a supplier.

Those handoffs are the real constraints. They show up in no dashboard, because they live between systems rather than inside any one of them. Classical automation could not touch them either — the inputs are unstructured and the decisions are judgment calls.

That is exactly where modern AI becomes economically viable. It reads unstructured language, classifies, extracts to a strict schema, reconciles against a system of record, decides under a confidence threshold, and escalates the remainder to a human with full context. Our job is to find those points, quantify them, and engineer them properly.

Unstructured intake
email, PDF, EDI, scans, calls, web forms
↓
Interpretation & extraction
OCR, vision-language model, validated output schema < 4 s
↓
Business rules & confidence gate
straight-through if in tolerance, else human escalation
↓
Write-back to the system of record
idempotent API calls, immutable audit trail
↓
Continuous throughput telemetry
lead time, straight-through rate, rework, drift alerts
How we work with you

On-site by default. Remote when the access model allows it.

Flow problems are observed, not described. Our consultants work inside your facility alongside the people doing the work, because the informal workarounds that keep a business running are never written down anywhere.

On-site engagement

Our default model. We are physically present on the plant floor, in the warehouse, at the accounting desk or in the dispatch office — observing cycle times, shadowing operators, and sitting in on the exception handling that nobody logs.

  • Direct time-and-motion observation of the constrained activity
  • Structured interviews with operators, supervisors and process owners
  • Workshops to validate the flow map with the people who live it
  • Recommended for discovery, and for any environment that is air-gapped, regulated or heavily physical

Remote delivery

Available where it is technically and contractually feasible. Remote work is only effective once we have real visibility into the systems that carry the process, so access provisioning is treated as a formal deliverable of the kick-off.

  • Access required: VPN or zero-trust broker, scoped SSO account, read-only database or API credentials
  • Telemetry required: audit-trail exports, event logs, mailbox or queue access for the process in scope
  • Environments: a sandbox or staging tenant for prototype work, separate from production
  • Typically used for build, integration and industrialization phases after an on-site discovery

Hybrid is the normal outcome

In practice most mandates run as on-site discovery and stakeholder validation, followed by remote engineering sprints with on-site checkpoints at each rollout gate. We scope the split explicitly in the statement of work, along with the exact access rights we need, who grants them, and when they are revoked at the end of the engagement.

Services

Six levers. One objective:
raise useful throughput.

We work in any organization where information technology carries the work — which is to say, everywhere. Manufacturing, distribution, professional services, construction, healthcare administration, finance, transportation, e-commerce and public-sector bodies.

Flow discovery & process mining

We pull event logs out of your systems, reconstruct the real path work takes, quantify queue time between activities, and expose rework loops and invisible handoffs.

process miningvalue stream mappingtheory of constraints

Intelligent process automation

End-to-end orchestration: event triggers, durable queues, idempotent retries, compensating transactions on failure. The model decides; the workflow engine guarantees execution.

durable orchestrationRPA + LLMidempotency keys

Intelligent document processing

Invoices, purchase orders, bills of lading, contracts, field reports, claims. Schema-constrained extraction with per-field confidence, cross-source reconciliation and a human review queue for the residue.

OCR + vision modelsstrict JSON schemathree-way match

Integration with systems of record

An integration layer over what you already run: REST and SOAP APIs, message queues, change-data capture on legacy databases, file-drop and EDI bridges. No forced replatforming.

APIs & webhooksCDClegacy adapters

Operational agents & copilots

Internal assistants grounded in your actual knowledge base — quotes, standards, SOPs, customer history — with source citations, tool permissions and hard guardrails on any state-changing action.

retrieval-augmented generationhybrid searchtool guardrails

Governance, security & compliance

Every automated decision traceable to its inputs and model version. PII minimization and redaction, in-region or on-premise hosting, least-privilege access review, documented rollback paths.

GDPR · PIPEDAimmutable audit logself-hosted inference
Full technical service breakdown
Method

We measure before we promise.

No performance commitment is made before the flow has been instrumented. The numbers produced during discovery become the baseline we are held against.

01
Weeks 1–4 · On-site immersion

We sit with your teams

Direct observation of the work, structured interviews with operators, and read-only access to application logs. We reconstruct the flow as it truly runs — including the undocumented workarounds that keep the business moving and appear on no process diagram.

02
Weeks 4–5 · Quantification

Ranked by constraint, not by trend

Every activity gets a volume, a cycle time, a queue time and an error rate. Interventions are ordered by throughput recovered per dollar invested, and we explicitly rule out what is not economically worth automating.

03
Weeks 5–11 · Prototype

A prototype on your real data

We build the most constraining link in an isolated environment, fed by a historical sample of your own records. Gate criteria: measured precision and recall, cost per transaction, and straight-through rate — evaluated on cases your team recognizes.

04
Weeks 11–20 · Industrialization

Progressive production rollout

Shadow mode alongside the human process first, then volume-staged cutover. Drift monitoring, confidence-threshold alerting, and a documented rollback procedure at every gate.

05
Ongoing · Handover

Your team keeps control

Runbooks, process-owner training, throughput dashboards. Code and infrastructure belong to you: you can replace us without losing the solution.

See the full method
Optimization examples

What this looks like in practice.

Representative engagement patterns, presented with the actual technical constraint and the indicators we tracked. Client organizations are anonymized.

Manufacturing · custom machined components

Shop-floor sequencing under changeover constraints

Constraint

The ERP sequenced production orders by due date only. Every material or tooling changeover imposed a 45-to-90-minute setup that the scheduler did not model. Planners were rewriting the sequence by hand in a spreadsheet twice a day, and the real cost of a bad sequence was invisible until the shift report.

Engineering intervention

Order extraction through the ERP API, a changeover cost matrix learned from 26 months of production history, then a constraint solver minimizing total setup time subject to due dates, machine capability and operator availability. A natural-language layer lets the planner state the day's real constraints in plain English; the accepted sequence is written back to the ERP with its justification attached.

constraint programmingERP API write-backlearned setup timesconversational interface

Measured indicators

+14%overall equipment effectiveness
−31%monthly machine setup hours
−4.5 daverage customer lead time
12 hmanual planning work removed per week
Professional services · accounting firm

Straight-through accounts payable

Constraint

4,200 supplier invoices arrived monthly by email in eleven layouts, including fax scans. Seven staff keyed data, matched purchase orders and worked exceptions. Median approval latency reached 9.4 days, forfeiting early-payment discounts and producing an unreliable cash-flow forecast.

Engineering intervention

Ingestion from the shared mailbox, attachment normalization, schema-constrained extraction with per-field confidence scoring, and three-way matching against purchase order and goods receipt. Invoices where every field clears its threshold and the variance stays within tolerance post automatically; everything else lands in a review queue, pre-filled, with the source region of the document highlighted for the reviewer.

document AIper-field confidence gatinghuman-in-the-loop queueaudit trail

Measured indicators

88%invoices posted with no human touch
1.6 dmedian approval latency, down from 9.4 d
−92%processing cost per invoice
0roles eliminated — staff redeployed to advisory work
Explore all eight engagement patterns

Technologies we operate daily

PythonPostgreSQL · pgvectorTemporaln8nAzure OpenAIAWS BedrockOllama · vLLMdbtDocker · KubernetesGrafanaSnowflakePower BI

Start by measuring one flow.

A 30-minute call is enough to determine whether your constraint is addressable with AI — and to tell you plainly if it is not.

Request a flow audit Understand the method