Our AI workflow automation services help businesses replace manual, repetitive processes with intelligent systems that operate continuously, learn from data, and scale with your operations. From a focused workflow audit to a fully integrated agentic workflow automation platform, you get senior practitioners, measurable outcomes, and full delivery ownership of every AI process automation system we build.
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80+
Workflows Automated
60+
Engineers In-House
96%
Client Retention
Built for teams at specific turning points.
Make the right call before you sign anything.
Most teams frame this as a tools decision before they understand the process. Here is the honest comparison across the dimensions that determine process automation ROI eighteen months in. Zethic builds the first two; we will tell you honestly when the third is the right call.
| What matters |
Recommended
Custom build
|
Common alternative
Off-the-shelf SaaS
|
Other path
Low-code platform
|
|---|---|---|---|
| Handles unstructured inputs | Documents, emails, images, and speech natively | Structured data and fixed UI paths only | Depends entirely on human judgment |
| Adapts to change | Models retrain; logic updates without full rebuilds | Brittle UI or format change breaks the bot | Process owner retrains the team |
| Scales with volume | Linear cost, non-linear output | License cost scales with bot count | Headcount scales with volume |
| Exception handling | Configurable fallback and human-in-the-loop | Falls to the manual queue silently | Already manual, no change |
| Auditability | Full trace log, decision reason, confidence score | Step log exists but is opaque to the business | Whatever people document |
| Time to first value | 4 to 8 weeks for the first production workflow | 6 to 12 weeks for a stable bot | Days, but the ceiling is low |
| Long-term cost (3 yrs) | Flat infrastructure plus improvement sprints | Per-bot licensing grows with scale | Headcount and process debt grow |
We design, build, and operate AI process automation systems, from a single intelligent workflow to a multi-system agentic platform. Start with the layer that delivers the most immediate value and expand from there.
We audit your current workflows to identify the highest-value AI workflow automation targets, integration complexity, and realistic ROI before any build commitment.
Process auditAutomation roadmapBuild vs buyROI mapping
We audit your current workflows to identify the highest-value AI workflow automation targets, integration complexity, and realistic ROI before any build commitment.
Beyond RPA, intelligent automation combines rules, AI classification, and decision logic to handle your full process spectrum, including unstructured data inputs and edge cases that break traditional bots.
AI classificationException routingHybrid rulesEvent-driven
Beyond RPA, intelligent automation combines rules, AI classification, and decision logic to handle your full process spectrum, including unstructured data inputs and edge cases that break traditional bots.
Agentic systems that interpret instructions, make decisions across steps, and handle ambiguity. Every agent ships with guardrails, eval harnesses, fallback logic, and observable decision traces.
LLM agentsMulti-agentHuman-in-the-loopDecision traces
Agentic systems that interpret instructions, make decisions across steps, and handle ambiguity. Every agent ships with guardrails, eval harnesses, fallback logic, and observable decision traces.
Pipelines that extract, classify, validate, and route document data from invoices, contracts, and forms, with confidence scoring and human review queues for low-certainty cases.
OCRData extractionClassificationConfidence scoring
Pipelines that extract, classify, validate, and route document data from invoices, contracts, and forms, with confidence scoring and human review queues for low-certainty cases.
The connection layer between your CRM, ERP, HRMS, and third-party APIs, built for resilience with proper error handling, retry logic, schema validation, and monitoring.
RESTWebhookiPaaSLegacy bridgeError handling
The connection layer between your CRM, ERP, HRMS, and third-party APIs, built for resilience with proper error handling, retry logic, schema validation, and monitoring.
Replace manual reporting cycles with automated pipelines that pull from operational systems and push results to the right surface: scheduled email, live dashboard, or embedded analytics view.
Automated pipelinesLive dashboardsAlertsEmbedded analytics
Replace manual reporting cycles with automated pipelines that pull from operational systems and push results to the right surface: scheduled email, live dashboard, or embedded analytics view.
You do not need to automate everything on day one.Tell us the process that costs you the most. We will show you what is possible.
What we automate, across your operations.
Different processes, same engineering discipline. Whatever the workflow, you get the same senior pod, the same eval cadence, accuracy benchmarks, and full ownership of the automation layer at handover.
Replace ten spreadsheets with one source of truth.
Extraction, validation, and three-way matching across high-volume invoices, with exception routing and a human review queue for genuine edge cases.
OCR and AI classification that turn contracts, forms, and PDFs into structured, validated data wired straight into your back-office systems.
Document collection, compliance checks, approval routing, and ERP provisioning handled end-to-end instead of over email threads.
Where money actually moves through your product.
Order capture, fulfilment triggers, and reconciliation automated across systems so revenue operations stop depending on manual data entry.
Agentic workflows that assemble quotes and proposals from your rules, pricing data, and templates, with approval recommendations built in.
Renewal tracking, dunning, and contract workflows that run on schedule and escalate the cases that actually need a human.
What your end users actually touch.
Agentic classification of inbound communications by intent, urgency, and product area, routed to the right team within seconds.
Automated pipelines that pull from operational systems and push results to scheduled email, live dashboards, or embedded analytics views.
Scheduled data extraction, transformation, and submission with a full audit trail for regulated workflows where precision is non-negotiable.
Automation for every operation.
Our technology
A model-agnostic, production-tested toolkit chosen for accuracy, resilience, and long-term maintainability. LLM agents, document AI, integration connectors, and observability, all owned by you at handover.
Compliant by design. Secure & Certified
Automation touches your most sensitive operational data. Every AI process automation system we build carries the controls, audit trails, and ownership guarantees that pass a security and compliance review.
We start with a structured workflow audit before recommending a single tool or framework. The AI process automation architecture follows the process, so what we build is scoped correctly from day one and does not need a redesign three months into production.
Your workflow definitions, integration credentials, and cloud infrastructure stay in your accounts. We do not build on proprietary platforms that create vendor dependency. Everything we deliver is portable, documented, and yours to operate independently.
A fast intelligent automation system that produces wrong outputs or fails silently is a production risk. We set accuracy benchmarks, define failure behaviour, build monitoring from day one, and make error rates visible before they become customer-facing incidents.
AI workflow automation projects are scoped and delivered by senior engineers and automation specialists. The people who assess your workflows are the people who build them, not a junior team handed the project after kickoff.
Selected work, real outcomes.
Selected AI workflow automation projects across financial services, logistics, healthcare, and enterprise operations.
View All Case StudiesOur achievements display our capabilities
Trusted voices. Real outcomes.
“We truly appreciated their dedication, technical expertise, and problem-solving approach.”
Young Onion
Department Head
“I was blown away by the knowledge the team had about creatives, e-commerce, website design, and optimization.”
Decathlon Sports India
Image Leader
“They have a good team of designers and project managers who help us with the designs using HTML, Angular, and React.”
Instarama
COO
“Their creativity stands out. A collaborative team that delivered high-quality solutions working closely with us.”
CodeGama LLP
Business Developer
“We truly appreciated their dedication, technical expertise, and problem-solving approach.”
Young Onion
Department Head
“I was blown away by the knowledge the team had about creatives, e-commerce, website design, and optimization.”
Decathlon Sports India
Image Leader
“They have a good team of designers and project managers who help us with the designs using HTML, Angular, and React.”
Instarama
COO
“Their creativity stands out. A collaborative team that delivered high-quality solutions working closely with us.”
CodeGama LLP
Business Developer
“The product has become more intuitive and user-friendly. Load times dropped significantly after their work.”
Qoruz
Co-Founder
“Simply put, the quality of their code is excellent. They integrated third-party software and ensured GDPR compliance.”
VIA IOM
Director
“What impressed us most was how well they understood our brand and translated it into clean, thoughtful designs.”
GD Farm Fresh
Director
“The product has become more intuitive and user-friendly. Load times dropped significantly after their work.”
Qoruz
Co-Founder
“Simply put, the quality of their code is excellent. They integrated third-party software and ensured GDPR compliance.”
VIA IOM
Director
“What impressed us most was how well they understood our brand and translated it into clean, thoughtful designs.”
GD Farm Fresh
Director
A four-phase model that delivers production AI workflow automation on a real timeline, starting with the process, not the platform.
Book a call{ 01 }· 1 to 2 weeks
We map your current process: inputs, outputs, decision points, exception paths, integration touchpoints, and volume. You get a prioritised AI process automation target list, a reference architecture, and a realistic delivery scope.
{ 02 }· 2-week sprints
We build the automation layer in agile sprints: extraction pipelines, agent logic, integration connectors, approval workflows, and the monitoring layer. Working demos every two weeks in a staging environment that mirrors production.
{ 03 }· Before go-live
We run the system against your real document samples and live data scenarios, measure accuracy against agreed benchmarks, conduct UAT, and resolve edge cases before production traffic hits.
{ 04 }· Launch and ongoing
Staged rollout with real-time monitoring, on-call handover, and a post-launch review cycle. We tune extraction models, adjust routing logic, and improve performance based on production signals, SLA-backed.
Engagement models, built to fit.
Senior automation engineers in your workflow, shipping every sprint. Choose the contract shape that matches your stage, your budget, and how much in-house automation capability you already have.
A scoped automation build with a defined deliverable, timeline, and price. Best for a first workflow, a single extraction pipeline, or a use case with a clear definition of done.
A senior automation pod embedded in your tools and rituals, shipping every sprint. Best for teams rolling out AI process automation across multiple workflows without a six-month hiring cycle.
AI workflow automation uses machine learning, large language models, and intelligent rules to perform operational tasks that previously required human judgment: reading documents, classifying requests, routing decisions, extracting data, and triggering downstream actions. Unlike traditional rule-based automation, AI process automation handles unstructured inputs, adapts to variation, and improves with use.
RPA executes fixed, rule-based sequences on structured data and predictable UI paths. It works for stable, high-volume processes but breaks when formats change or exceptions arise. AI workflow automation handles unstructured inputs, learns from examples, and manages edge cases, making it the right choice for document-heavy, judgment-dependent, or variable workflows where RPA cannot operate reliably.
The strongest candidates are high-volume, repetitive processes currently handled by people following a consistent logic. Document intake, approval routing, data entry and reconciliation, customer query triage, compliance monitoring, and reporting automation are all strong starting points. A workflow assessment identifies which of your processes offer the best process automation ROI.
A focused single workflow, extraction pipeline, approval routing system, or reporting automation typically takes four to eight weeks from assessment to production. A multi-workflow or agentic workflow automation system runs for eight to sixteen weeks. The assessment phase gives you a firm timeline before any build commitment.
You do, fully. The workflow definitions, integration credentials, cloud infrastructure, and model configurations all live in your accounts. We do not build on proprietary platforms that create vendor dependency. At handover, your team can operate, modify, and extend every AI process automation system we have built.
Every extraction or classification system ships with a defined accuracy benchmark, a test set drawn from your real data, and a confidence-based human-in-the-loop review queue for low-certainty cases. We do not deploy intelligent automation that fails silently. The system routes uncertain cases to a human reviewer appropriately.
Yes. We offer SLA-backed monitoring, on-call response, model performance reviews, and improvement sprints after launch. AI workflow automation systems drift when the real world changes. We build in observability to catch that early and the engagement model to act on it quickly.
Yes. Most of our clients have at least one legacy system in the chain: an on-prem ERP, a mainframe, or an older API with limited documentation. We build the integration layer around what exists, using screen capture, database-level connectors, file-based pipelines, or API wrappers. Integration complexity is scoped accurately before any build begins.
Cost transparency, before the call.
Most agencies will not put a number on the page. Here is the honest band by automation scope, plus the five things that actually move the number once we scope your specific workflows.
| Tier comparison | Automating one high-cost process Single workflow automation $15K - $45K ₹12L - ₹36L |
Most chosen
Connecting several processes Multi-workflow / agentic system $45K - $150K ₹36L - ₹1.2Cr | Automation across teams Enterprise automation platform $150K - $400K ₹1.2Cr - ₹3.2Cr | Ongoing capacity Embedded automation pod from $18K / month from ₹15L / month |
|---|---|---|---|---|
| Timeline | 4 to 8 weeks | 8 to 16 weeks | 5 to 9 months | Sprint-by-sprint |
| What you get |
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The number of decision points, exception paths, and approval steps in the workflow drives how much agent logic and edge-case handling the system needs.
How much document extraction, classification, and validation your inputs need, and how varied the formats are, before a model can process them reliably.
Every external system (CRM, ERP, HRMS, legacy API) adds discovery, contract testing, error handling, and monitoring to the connection layer.
The higher the precision requirement, the more eval work, benchmarking, and human-in-the-loop checkpoints the automation needs before go-live.
SOC 2, HIPAA, RBI, DPDP, and similar add architecture constraints, audit work, PII handling, and pre-launch reviews to the scope.
Bands include process discovery, engineering, evals, integration, and PM. Model and inference fees, hosting, and third-party licenses are billed at cost.
Tell us the process, the volume, and where the current approach is reaching its limit. A senior automation specialist replies within one working day. No SDR, no slideware, no twelve-step qualification.
Step 1 - Tell us where you are
Which AI workflow automation candidates cost you the most time or carry the most risk. Share the context. We sign an NDA before any specifics.
Step 2 - Speak to a specialist
A senior automation engineer joins within two working days to map your process, your integration landscape, and the shortest path to working AI process automation.
Step 3 - Get a real plan
A workflow architecture, a scope band, and an engagement model matched to your stage. A working intelligent automation system, not a proof-of-concept demo.
Tell us the process, the volume, and where the current approach is reaching its limit. A senior automation specialist replies within one working day. No SDR, no slideware, no twelve-step qualification.
