We build practical AI-powered workflows that help teams classify, summarize, route, draft, analyze, and act — while keeping people in control of the decisions that matter.
AI is most valuable as a first-pass layer — handling classification, summarization, drafting, and routing — so your team can focus on the work that actually requires human judgment.
These are the AI automations we build most often — connected to real systems, with human review built in where it matters.
AI reads incoming quote requests from email, web forms, or chat — extracts product, quantity, pricing context, and creates a structured CRM record.
Classify inbound emails by type, urgency, and sentiment — route to the right team and suggest a draft response based on CRM history.
Automatically summarize long Slack threads, call transcripts, or support tickets into a concise brief for the next person in the workflow.
Build an internal AI assistant that answers questions about SOPs, pricing policies, product specs, and process documentation — instantly.
Use AI to identify duplicate accounts, enrich missing fields, standardize naming conventions, and flag records that need human review.
Automatically research new accounts and contacts — company size, tech stack, recent news, decision makers — and populate CRM fields before the first call.
Extract structured data from contracts, invoices, purchase orders, and proposals — and push the output into CRM or ERP records.
Summarize billing exceptions, contract discrepancies, and quote approval holds for deal desk review — surfaced in Slack with one-click resolution.
Every AI workflow Pallvera builds includes explicit review gates — typically Slack messages where a human can approve, reject, or edit before the system takes action. AI does the heavy lifting. People make the calls.
This design also makes AI workflows easier to trust, audit, and improve over time. You can see what the AI produced, how people responded, and where the process needs tuning.
Discuss AI workflow designAI workflows only create value if they connect to the systems your team depends on. Pallvera builds AI that reads from and writes to real business systems.
Slack is where your team already works. Pallvera builds AI workflows that surface AI output, approval requests, and action items directly in Slack — so people do not need to switch tools to act on AI recommendations.
AI workflows that touch customer data, financial records, and internal systems require careful design. Pallvera builds AI with data governance, access controls, audit logging, and appropriate data boundaries from the start.
AI systems only access the data they need. We design explicit permission scopes and data boundaries from the start.
Every AI action is logged — what was input, what was output, what the human decided, and when. Full traceability.
Explicit approval steps before AI output triggers real system actions. AI assists; humans decide.
We design clear limits on what AI can and cannot do — so the system does not drift or take unexpected actions.