n8n, Make, Zapier, and custom Python — combined with OpenAI / Claude / LangGraph so the workflows your team hated doing now run 24/7.
Email triage, document processing, lead qualification, support automation, multi-system integrations. 10–40 hours saved per workflow, per week.
From email triage to multi-agent autonomous workflows — automation that pays for itself in month one.
AI reads incoming email, classifies intent, drafts a reply, creates a CRM/helpdesk record, and routes anything needing human attention.
PDFs, contracts, invoices, ID cards, forms — extracted, validated, pushed into ERP / CRM / data warehouse with full audit trail.
Lead-form / inquiry → AI qualification → CRM enrichment → meeting booking → drip nurture — fully automated, with rep-only escalation when AI confidence is high.
Ticket comes in → AI summarises → categorises → drafts reply → checks knowledge base → escalates with full context if needed.
Approval workflows with AI smart steps — expense triage, leave approval, onboarding checklists, vendor onboarding, contract review.
Connect anything to anything — ERP ↔ CRM ↔ helpdesk ↔ accounting ↔ marketing ↔ data warehouse — with AI normalising and de-duplicating along the way.
AI-enriched data pipelines — categorise transactions, summarise documents into search indexes, auto-tag CMS content, populate vector DBs for RAG.
LangGraph / CrewAI / AutoGen agents that take a high-level goal and execute multi-step workflows with tool use, memory, and human-in-the-loop checkpoints.
One workflow built end-to-end in 2–3 weeks. Best for proving ROI before scaling.
5–10 high-ROI workflows shipped in 8–12 weeks. Replaces the work of 1–3 full-time roles.
Ongoing — we ship new workflows monthly, maintain existing ones, and tune AI as your business evolves.
We shadow your team, map the 10–20 workflows that consume the most human hours, and rank by ROI × feasibility. Output: an automation roadmap.
Per workflow: trigger, AI steps, integrations, exception handling, human-in-the-loop checkpoints, success metric. We design before we build.
Built on n8n / Make / Zapier — or custom Python where the workflow demands it. AI steps with proper prompts, evals, and cost guardrails.
Run alongside the manual process for 1–2 weeks. Measure accuracy, time saved, error rate. Tune until the workflow is unambiguously better than human.
Cutover with full observability. Monthly retainer: monitor, tune AI prompts, ship new workflows, upgrade models — keep the savings compounding.
Most automation shops know Zapier but not AI. Most AI shops know LLMs but not enterprise integrations. We do both production-grade.
We don't automate everything — we automate the workflows with the biggest hours-saved-per-week × success-probability. Numbers backed up by audit.
Source in your GitHub, workflows in your n8n / Make / Zapier account, AI keys in your name. We don't lock anything behind our login.
Zapier for simple integrations, n8n for self-hosted complex flows, Make for visual orchestration, custom Python when the workflow demands it. We pick — not push.
We add approval / review steps for high-stakes workflows (payments, contracts, customer-facing). AI for speed, human for safety.
Token budgets per workflow, model routing (Haiku/Mini for simple, GPT-4o/Claude for complex), caching. Automation must pay for itself month one.
Combining traditional integration tools (n8n, Make, Zapier) with AI steps (LLMs) so workflows that previously required human judgement — reading emails, drafting replies, categorising tickets, extracting data — run automatically. Humans only review exceptions.
Zapier: fastest for simple integrations between SaaS apps. Make: best visual orchestration for medium-complex flows. n8n: self-hosted, code-friendly, best for complex or data-sensitive flows. Custom Python (FastAPI/LangGraph): when workflows need full programmatic control, stateful agents, or strict performance. We pick per workflow.
Simple workflows (lead routing, ticket summarisation): 1–2 weeks. Medium (multi-step approval with AI steps): 2–4 weeks. Complex (multi-agent with tools, cross-system data flows): 4–8 weeks. Most clients ship 5–10 workflows in 8–12 weeks.
Pilot workflow: ₹1L–₹3L ($1.2K–$4K) build + ₹5K–₹25K/month ($60–$300) hosting/AI. Automation sprint (5–10 workflows): ₹6L–₹18L ($7K–$22K). Automation retainer: ₹40K–₹2L/month ($500–$2.5K) for ongoing ship+maintain.
Yes. We routinely connect Odoo, SAP, Microsoft Dynamics, NetSuite, HubSpot, Salesforce, Zoho, Pipedrive, Zendesk, Intercom, Freshdesk, Notion, Airtable, Google Workspace, Microsoft 365, and custom systems via APIs/webhooks.
We've seen single workflows save 10–40 hours/week per team — at typical ops salary that's ₹2L–₹8L/month per workflow. A pilot pays back in 1–3 months. We agree on a measurable ROI metric per workflow before building.
Yes occasionally — that's why we add: (1) human-in-the-loop checkpoints for high-stakes steps, (2) confidence thresholds that route low-confidence cases to humans, (3) automated evals on every prompt change, (4) full observability via Langfuse/LangSmith to spot drift.
Yes. Hosted on AWS / Azure / GCP / Vercel with multi-region failover where required. Retainer plans include SLA-backed monitoring and incident response.
Odoo 20 AI now runs on IAP credits at EUR 1 each. See which features use credits, what scanning, enrichment and SMS cost, and a sample monthly budget.
Free 30-minute automation audit. We'll rank your highest-ROI workflows and send a fixed-price proposal within 48 hours.
