Agentic AI for enterprise outcomes

On Blits.ai this is an AI agent with custom functions that call the retailer's order management, carrier tracking and returns APIs (REST calls with their own authentication and limits), and a knowledge base with the approved delivery, returns and warranty content, retrieved with hybrid search. Return eligibility and refund rules run as deterministic steps in a flow or inside the function, so the model explains the decision rather than making it; larger refunds can go through an agentic workflow with human in the loop approval above a set threshold.

The same agent serves web chat, WhatsApp, email and voice, and a mobile app through the REST or WebSocket API channel; the chat widget can show orders and receipts as rich cards. Guardrails check input and output, PII masking and card number tokenization happen at the gateway, and human handover escalates the conversation to the service team, including through Salesforce, Freshdesk or Zoho SalesIQ. Test suites run multi turn order and return conversations as regression tests after each change, and monitors check the order lookup against a test order on a schedule. The platform is model agnostic, so the model can be chosen or switched per agent.

On Blits.ai this is an agentic workflow triggered through the API when a claim is opened. An AI agent reads the claim and its documents through the knowledge base document ingestion (PDF, images and Outlook email files), writes a summary with structured output, and calls custom functions that fetch cover and limits from the policy system, pull fraud and severity scores, and write the routing decision back to the claims system.

Human in the loop approval holds any payment above the configured threshold for a handler, and the tool execution policy limits which systems the agent may change. Every run has a full audit trail, test suites grade summaries and routing against labeled historical claims on each change, and monitors run scheduled checks against the agent and alert by email or webhook when an expectation fails. The platform is model agnostic. Run Blits.ai in our cloud in the EU, Qatar, Singapore, the UAE, the US or Australia, in your private cloud, or fully on premises to meet data residency requirements.

On Blits.ai this is an AI agent in the Microsoft Teams or Slack channel, with custom functions that call the identity provider and ITSM APIs (REST calls with their own credentials and limits). The integration catalog includes systems such as ServiceNow, Jira and Okta, and Freshdesk is available as a ready made tool. How to questions are answered from a knowledge base of IT articles with hybrid retrieval, and a flow handles the deterministic steps of a reset, including an authentication step, before the agent is allowed to call the reset function.

Agentic workflows can run multi step requests such as provisioning, with human in the loop approval above a set threshold and a tool execution policy that limits which tools the agent may use. Every run has an audit trail. Guardrails check input and output, PII masking keeps personal data out of prompts, and human handover passes the conversation to an analyst.

Test suites run automated conversation evaluations of the agent before changes go live, monitors run scheduled health checks, and analytics show volumes, recognition rate and satisfaction. Model agnostic routing is available, and administrators sign in to the platform with single sign on through Microsoft Entra or Google. Run Blits.ai in our cloud in the EU, Qatar, Singapore, the UAE, the US or Australia, in your private cloud, or fully on premises.

On Blits.ai this is an agentic workflow. Invoices arrive through the email channel, where a dialog flow triggers the workflow, or directly through an API token. An AI agent with structured output returns the invoice fields, and custom functions look up the vendor master, purchase orders and goods receipts in the ERP (for example through the SAP or NetSuite connections in the integration catalog) and create the posting proposal. Contract terms and coding rules sit in the knowledge base with hybrid retrieval.

Human in the loop confirmation stops the posting action above a configurable threshold for a person to approve or reject. Other routing rules, such as sending every invoice with a changed bank account to a person, are built with custom functions in the workflow, and the ready made Microsoft Teams tool can notify the approver. Every run keeps a full audit trail, test suites replay a labeled set of invoices before each change goes live, and monitors run scheduled checks against the agent and alert on failure.

On Blits.ai this is an AI agent with custom functions that call the airline's reservation, reaccommodation, ticketing and baggage APIs, combined with a knowledge base that holds only approved policy and passenger rights content, retrieved with hybrid search. The rebooking and refund journeys run as flows with deterministic steps and an authentication block, so the offer shown is the offer the rules allow; the agent explains the options and answers open questions. Agentic workflows with human in the loop approval handle refunds or vouchers above a threshold, and the payment service collects fare differences with card tokenization.

The same agent serves web chat, WhatsApp, SMS and voice, and the airline's own app through the API channel, with streaming speech on the phone for passengers who call. Guardrails and PII masking check every turn, human handover passes the summary and the options already offered to the contact center, test suites replay disruption scenarios per market before every change, and monitors run scheduled health checks against the live agent. Analytics show interactions, satisfaction and top intents per channel, custom dashboard widgets can track handovers per disruption type, and the platform is model agnostic. Run Blits.ai in our cloud in the EU, Qatar, Singapore, the UAE, the US or Australia, in your private cloud, or fully on premises.

On Blits.ai this is an agentic workflow triggered through the API when a new dispute arrives from the network systems. Custom functions fetch transaction, authentication and delivery evidence, the network rules and evidence maps sit in the knowledge base with hybrid retrieval, and an AI agent with structured output builds the package and drafts the rebuttal. Agentic tasks recheck deadlines on a schedule.

Human in the loop approval holds contested and high value cases for an analyst. The custom functions return masked card data, so the agent sees only what each step needs. Each run keeps a full audit trail, and test suites replay past disputes with known outcomes before rule or prompt changes go live. A customer facing agent on the same platform can open the dispute and show its status to the cardholder; in that chat, card numbers the cardholder types are detected and tokenized at the gateway.