Voice AI and WhatsApp Automation
Automate customer and operational conversations where they make sense, including reminders, support, verification, updates, and assisted journeys.
Sprio helps retailers, marketplaces, D2C brands, and e-commerce teams connect customer communication, product data, order systems, support workflows, and AI automation into one operating layer.
Voice AI and WhatsApp automation are part of Sprio's product layer. The larger layer is enterprise AI services: RAG, agents, integrations, governance, and managed AI operations.
Automate customer and operational conversations where they make sense, including reminders, support, verification, updates, and assisted journeys.
Use proprietary documents, records, policies, product data, and knowledge bases so AI answers from the business context, not a generic prompt.
Build agents that choose the next step, prepare actions, handle exceptions, and work across teams with human review where needed.
Connect AI with CRM, ERP, helpdesk, databases, documents, dashboards, cloud systems, and industry platforms.
Add role-based access, source grounding, approval paths, audit logs, fallback rules, and deployment controls around sensitive workflows.
Monitor, evaluate, optimize, and maintain AI systems after launch so they keep working as data, teams, and business rules change.
Sprio combines communication products with AI engineering services so Retail and E-commerce teams can move from isolated use cases to working systems.
Turn proprietary documents, data, and knowledge into searchable intelligence, decision support, and workflow context.
Build agents and multi-step workflows that execute processes across CRMs, ERPs, databases, documents, and enterprise applications.
Customize prompts, retrieval, evaluation, model behavior, and domain-specific AI systems for enterprise use cases.
Deploy, monitor, evaluate, scale, and improve AI systems after they leave the prototype stage.
Connect AI with existing architecture while maintaining access control, observability, auditability, and human oversight.
AI becomes useful when it addresses the messy parts of the business: data, documents, decisions, handoffs, and production reliability.
Customer history, product data, tickets, payments, shipments, returns, and campaign data sit in separate tools.
Teams answer the same questions about delivery, returns, refunds, sizing, availability, and order changes every day.
Product attributes, reviews, inventory, recommendations, and merchandising rules are difficult to use consistently.
COD checks, RTO risk, failed delivery, refund review, and return eligibility still need manual coordination.
Repeat purchase, loyalty, complaints, browsing, and abandoned cart signals are not converted into useful actions quickly enough.
These are serious workflow areas where Sprio can combine communication AI, RAG, agents, integrations, and managed AI operations.
Help customers compare products, ask fit or compatibility questions, and find the right item faster.
Resolve order status, returns, refunds, exchange, warranty, and product questions using live business context.
Clean product attributes, enrich descriptions, classify items, summarize reviews, and improve product discovery.
Check policies, order history, product condition, reason codes, and route approvals or pickups.
Prepare category insights, stock alerts, product gaps, pricing notes, and campaign recommendations.
Turn purchase, support, loyalty, review, and browsing signals into segments and next actions.
Storefront, OMS, PIM, CRM, payment gateway, courier APIs, warehouse data, reviews, tickets, product catalogues, loyalty data, and campaign tools.
Sprio maps the documents, databases, applications, conversations, records, and knowledge sources that already hold business context.
Approved information is organized so AI can retrieve the right context instead of guessing from a generic prompt.
Models are selected, prompted, evaluated, and adapted around the questions, documents, and decisions in the workflow.
Agents use the knowledge layer and approved tools to prepare answers, trigger actions, and route exceptions.
The result is not only an answer. It can become an update, task, approval, report, alert, or business workflow.
Enterprises already have software. The gap is the work people still do between those systems.
Sprio builds the intelligence layer between customer requests, internal tools, documents, approvals, and enterprise applications.
Agents retrieve context from approved data sources before preparing a response or action.
Human review can be required for high-risk, unclear, regulated, or high-value decisions.
Outcomes are written back to the systems your team already uses, so reporting and follow-up stay clean.
Sprio can combine RAG, LLMs, multi-agent systems, integrations, MLOps, and governance when the problem is larger than one chatbot or one automation.
Use the company's real knowledge, documents, records, and operating history.
Split work across specialized agents for retrieval, drafting, checking, routing, and reporting.
Connect AI to the systems where work is assigned, approved, updated, and measured.
Monitor quality, cost, access, accuracy, failures, and user feedback after launch.
The value is not in saying AI is available. The value is in reducing delay, manual work, risk, and disconnected decisions.
Deflect repeated order, return, refund, and product questions with reliable answers.
Help shoppers choose products faster and recover abandoned journeys with better context.
Act earlier on risky orders and automate clean return decisions.
Make product data easier to search, compare, enrich, and reuse.
Let teams manage more orders, queries, and campaigns without adding the same amount of manual work.
Sprio can connect modern SaaS, older enterprise software, documents, databases, communication systems, cloud infrastructure, and industry platforms.
Shopify, WooCommerce, Magento, custom storefronts, order management, and inventory tools.
PIM, catalogues, attributes, images, reviews, pricing, and availability data.
Helpdesks, tickets, customer profiles, loyalty systems, complaints, and feedback.
Payment gateways, refund status, COD checks, invoices, and reconciliation data.
Courier APIs, delivery status, NDR data, pickup scheduling, and RTO signals.
Warehouses, analytics tools, vector databases, LLMs, cloud services, and dashboards.
Sprio can help build, deploy, run, monitor, and improve AI systems after launch.
Ongoing monitoring for quality, latency, cost, usage, failures, and business outcomes.
Keep sources fresh, structured, permissioned, and useful as policies, products, and documents change.
Review workflow performance, adjust rules, improve prompts, and expand agents into adjacent processes.
Maintain logs, approval rules, access controls, evaluation sets, fallback paths, and release discipline.
Sprio brings AI communication products and enterprise AI services together so the whole problem can be solved, not just one visible surface.
AI voice and messaging products handle real customer and operational interactions at scale.
RAG, enterprise data, documents, and LLMs turn proprietary knowledge into useful context.
AI agents, models, and enterprise intelligence help choose the next best action.
Agentic workflows and system integrations update tools, create tasks, send outputs, and route approvals.
MLOps, LLMOps, monitoring, and managed services keep the AI useful after launch.
Customer data, payment context, return decisions, and marketing workflows can be governed with access controls, consent handling, audit trails, and approval gates.
Control who can ask, view, approve, export, or trigger actions inside an AI workflow.
AI systems can be designed for cloud, private cloud, VPC, or on-premise requirements depending on scope.
Critical answers can be tied to approved documents, data sources, and business rules.
Track actions, approvals, failures, user feedback, model behavior, and workflow outcomes.