The AI that turns complex into easy

ScaleLabs builds custom, production-grade software that automates internal business processes end to end. That usually means replacing “people-powered” workflows trapped in email threads, spreadsheets, PDFs, and legacy tools with a single system that routes work automatically, enforces rules, and creates visibility.

Common automations we deliver:
‍Intake + onboarding: customer/vendor onboarding, KYC, compliance packets, document collection, approvals
‍Operations + dispatch: job routing, scheduling handoffs, QA checks, exception handling
‍Finance ops: invoice validation, PO matching, collections workflows, vendor payments, reconciliation
‍Sales + account workflows: quoting, renewals, customer requests, SOW generation, status updates
‍Data + reporting: consolidating multi-system data into a clean operational dashboard (not another BI graveyard)

Most projects include AI agents for tasks like extraction, classification, summarization, routing, and proactive follow-ups—always with guardrails and audit trails so the system is reliable, not “mysterious.”

Three big differences:

‍1) We operate like an in-house technical team, not a “ticket-taking” vendor.
‍
We help you define the workflow, map edge cases, design the system, ship it, and support it. You get senior product + engineering leadership without building an internal org from scratch.

‍2) We thrive in complex environments.
If your process touches 5–10 systems, involves approvals, exceptions, messy documents, and multiple teams—this is where we’re best. Off-the-shelf tools often fail when reality gets complicated.

‍3) We deliver automation that sticks.
A lot of automation dies in week 6 because it’s brittle, lacks ownership, or doesn’t match how teams actually work. We build software with: clear roles + permissions, human-in-the-loop checkpoints where needed, monitoring, logs, and measurable SLAs, ierative rollouts so adoption stays high.

Bottom line: you get real operational software, not a prototype, and not a “tool you now have to become an expert in.”

Most successful projects follow a structured path:

‍Week 1–2: Discovery + workflow mapping
We map your current process, identify failure points, quantify time/cost, and define the “to-be” workflow. You’ll walk away with a clear scope, timeline, and ROI model.

‍Week 3–6: MVP build + integration foundation
We ship a first working version quickly so stakeholders can react to something real. We also set up core integrations (CRM/ERP/document systems) early so we’re building in the real environment.

‍Week 7–10: Automation depth + AI agents + edge cases
This is where we add the intelligence: routing, extraction, validations, exception handling, approvals, notifications, and role-based dashboards.

‍Week 10–12: Pilot + rollout + training
We deploy to a pilot group, measure improvements, then roll out broader with training and feedback loops.

After launch, we typically run 30–60 days of hypercare, then shift to a light ongoing support + optimization cadence.

Timelines depend on workflow complexity and integration depth, but here are realistic ranges:

‍Workflow automation MVP: 4–8 weeks
‍Deeply integrated, multi-department system: 8–14 weeks
‍Enterprise-grade rollout across sites/regions: 12–20 weeks

ROI tends to show up fast because we target workflows with recurring labor cost and high friction.

Typical outcomes we design for (varies by industry/process):
‍30–60% reduction in manual admin time on the targeted workflow
‍2–10x faster cycle times (onboarding, approvals, document turnaround, etc.)
‍Lower error rates through validation, automation, and consistent routing
‍Higher customer satisfaction due to transparency and fewer “what’s the status?” touches

Many clients see payback within 3–6 months when the workflow touches revenue, compliance risk, or high-volume ops.

We build for real businesses—security and compliance are not optional.

‍Security standards we commonly implement: role-based access control (RBAC) and least-privilege permissions, audit logs for key actions and data changes, encryption in transit and at restSSO (SAML/OAuth) where required, secure secrets management and environment separation (dev/stage/prod)

‍AI safety and governance: we use guardrails (allowed actions, confidence thresholds, approvals), sensitive data handling policies (redaction, retention controls), human-in-the-loop checkpoints for high-risk decisions, transparent prompts/outputs and traceability for critical steps

‍Integrations:
We regularly integrate with CRMs, ERPs, document systems, and internal databases via APIs and webhooks. If you’re dealing with legacy tools, we’ll design around constraints using reliable integration patterns—without building a fragile house of cards.

If needed, we can align to your organization’s security review process and provide documentation for IT, procurement, and compliance teams.