“I need to change my shipping address.”
Customer · authenticated session
AI services
Agentic assistants that understand intent and next steps
We build conversational experiences for B2B teams where the goal is resolution, not a generic chat. Assistants route requests, run agent workflows against your APIs and knowledge, and lighten the contact centre by automating the work that does not need a human on the line.
Built for operations, not endless improvisation
A generative-only chat layer can sound fluent while getting facts wrong. Our focus is different: structured intent, grounded replies, and agents that take actions so customers leave with outcomes, not paragraphs.
Intent and actions, not open-ended chats
The assistant classifies what the customer needs, pulls the right account and order context, and follows playbooks your business already trusts. It is not a novelty that improvises answers from thin air.
Agents that do work in your systems
Behind the conversation sits an agent layer that can look up orders, create tickets, update CRM fields, and trigger notifications. Repeatable problems close in-channel so your team handles exceptions, not every keystroke.
How agent workflows carry a conversation
Each turn can be more than text. The system interprets intent, plans steps, calls tools with your rules, and decides when to resolve in self-service or pass a concise package to a live agent.
Use case
“Action-first” autonomous support agents
Simple chatbots only answer questions. Agentic assistants resolve tickets end to end.
This is the shift from FAQs to doing the work: authenticate the customer, read live order state, call the right APIs, sync downstream systems, and close the loop in chat. Mid-to-large e-commerce, software vendors, and logistics operators feel this first: high ticket volume, clear policies, and systems that already expose APIs.
Example: a customer writes, “I need to change my shipping address.” A thin FAQ flow only links to a portal. An action-first agent verifies the session, checks Shopify or your storefront layer to confirm the order is still open, validates against your ERP or OMS rules, updates the address through a secured integration, pings the warehouse or WMS if your process requires it, and replies with confirmation. The tier 2 support ticket never needs a human if policy allows fully automated resolution.
Where it lands
- E-commerce
- Software & SaaS
- Logistics & fulfilment
Commerce stack (example)
Shopify
Order open · not shipped · address editable via API
ERP / OMS
Rules, cut-offs, warehouse routing
Update address via API · confirm warehouse · notify customer
Tier 2 ticket resolved in-channel
“All set. Your order will ship to the new address. Confirmation emailed.”
Grounded reply · audit trail retained
Integrations
Commerce platforms we support
Storefronts, carts, and payments your agents can call into. This is a representative set; we also wire up custom stacks and headless builds.
Knowledge
RAG and your document library, in plain terms
Retrieval-augmented generation means the assistant looks up relevant chunks from your approved knowledge before it answers. Think of it as giving the assistant a curated library: product sheets, SOPs, policy PDFs, and support macros that you already maintain. The model still composes natural language, but it is anchored to those passages, which cuts hallucinations and keeps answers aligned with how your business actually works.
For B2B buyers, the value is speed and consistency: the same clause in a contract or SLA shows up the same way for every rep and customer, and updates roll out when you refresh the source documents, not when someone remembers to retrain a script.
What you typically index
- Internal FAQs, troubleshooting trees, and escalation rules.
- Product and packaging documentation with version dates.
- Regional or segment-specific policies so answers stay compliant.
- Hand-off summaries so live agents see what self-service already tried.
Contact centre load, without lowering the bar
The business case is straightforward: fewer redundant contacts, faster resolution for straightforward issues, and specialists free for revenue, retention, and complex cases.
Deflect repeat volume
Status, policy, and how-to questions absorb a large share of queues. When the assistant resolves them with verified data, average handle time and abandon rates improve without lowering quality.
Cleaner hand-offs
When someone does need a person, the thread arrives with intent, entities, and attempted actions. Agents start ahead of the first hello instead of re-asking for an order number.
Governed answers
Responses draw from approved sources and tool results, with guardrails on tone, eligibility, and escalation. That is how you scale conversations without scaling risk.
Ready to design your assistant?
We map intents, integrate tools, and stand up grounded answers with a clear path to production. Share your channels, volumes, and systems, and we will propose a phased rollout your teams can adopt.
Prefer email first? info@sdsclick.io