Workflow Automation with AI
End-to-end automation of complex multi-step business workflows using AI decision-making. We map your processes and design intelligent pipelines that adapt to exceptions and edge cases.
We design and deploy intelligent automation workflows that eliminate repetitive work, reduce errors, and free your team to focus on what matters — saving an average of 70% in manual processing time.
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Independently audited, certified and built to standards you can check

AI automation replaces repetitive manual workflows with intelligent pipelines that classify documents, route emails, and make decisions at scale. Codazz delivers AI automation services combining LLMs and RPA — document extraction, data pipelines, and workflow orchestration that save 50–80% of processing time across 80+ deployments.
End-to-end automation of complex multi-step business workflows using AI decision-making. We map your processes and design intelligent pipelines that adapt to exceptions and edge cases.
Automate extraction of structured data from invoices, contracts, forms, and reports using LLMs and OCR. Reduce manual data entry by up to 95% while improving accuracy.
AI-powered email triage, drafting, and routing. Auto-classify incoming messages, generate context-aware responses, and escalate priority issues without human intervention.
Intelligent ETL pipelines that clean, transform, and enrich data using AI models. Handle unstructured inputs, detect anomalies, and maintain data quality automatically at scale.
Replace manual approval workflows with AI-driven decision engines. Automate credit scoring, content moderation, lead qualification, and compliance checks with explainable AI.
Combine traditional Robotic Process Automation with AI intelligence to handle both structured and unstructured tasks. We integrate with UiPath, Automation Anywhere, and custom RPA stacks.
Our Work
200+ products shipped across fintech, healthcare, e-commerce, and SaaS — built to scale, designed to convert.

Web Design
A marketing site for an interior design studio, rebuilt on Next.js to load fast on mobile and convert visitors into enquiries.

Healthcare
A patient management platform handling scheduling, records and clinician-patient messaging for a healthcare provider.

E-Commerce
A fitness e-commerce storefront built on Next.js with Shopify as the commerce backend and Stripe handling payments.

Logistics
A delivery management platform with live vehicle tracking, route planning and customer-facing shipment status.

Logistics
A freight management platform for an established trucking operator, covering load tracking and job records.

SaaS
A multi-tenant SaaS platform that aggregates business reviews across sources and surfaces them in one dashboard.
We map your existing workflows, identify bottleneck tasks, quantify time costs, and rank automation opportunities by ROI potential and implementation feasibility.
We design the automation architecture — defining triggers, AI decision points, data flows, exception handling, and human-in-the-loop checkpoints for edge cases.
We build and integrate the automation system with your existing tools (CRM, ERP, Slack, email), train AI components on your data, and configure monitoring dashboards.
Post-launch, we monitor accuracy and throughput, retrain models as data drifts, and continuously add new automation use cases to grow your ROI over time.
The best candidates are high-volume, repetitive tasks with clear rules or patterns — like data entry, invoice processing, email triage, report generation, and lead qualification. Processes that currently consume significant manual hours but don't require nuanced human judgment are ideal starting points. We conduct a process audit to rank your opportunities by ROI.
Traditional RPA follows rigid rules and breaks when interfaces or formats change. AI automation adds intelligence — it can understand unstructured data (PDFs, emails, images), make contextual decisions, handle variability, and improve over time through learning. We often combine both: RPA handles structured UI interactions while AI handles the cognitive tasks.
We design explicit exception handling into every workflow — with confidence thresholds, fallback logic, and human-in-the-loop escalation for cases where the AI is uncertain. You get a dashboard to review flagged exceptions, and we use those cases to continuously improve model accuracy over time.
Most clients see 50–80% reduction in manual processing time for automated tasks, with payback periods of 3–9 months. One document processing client reduced invoice processing costs from $12/invoice to $0.80. ROI depends on volume, current labor cost, and process complexity — we model this during the audit phase before you commit.
A focused, well-scoped automation can be live in 4–6 weeks: 1–2 weeks for process analysis and design, 2–3 weeks for development and integration, and 1 week for testing and go-live. More complex multi-system automations typically take 8–12 weeks. We prioritize getting a first win into production quickly, then expand from there.
Let's discuss your automation project and build something great together.