Answer with Iris
Freemium
HVAC, plumbing, electrical, roofing contractors
Support teams burn hours answering the same price and inventory questions because the answers live in spreadsheets that nobody can query without opening a file, scrolling, and guessing.
FrontierBase connects Excel files, CSVs, or Google Sheets to a chat interface — via an embeddable widget or REST API — and answers questions by retrieving the actual rows, not by paraphrasing what it thinks the data says. The vendor describes hybrid semantic and keyword search operating at the row level, which means the system pulls the specific record rather than summarizing the document. Response policies let you set tone and safety rules so answers stay inside the guardrails your business requires. The wall appears when your data lives outside spreadsheets: no database connectors, no structured API ingestion, no support for unstructured documents — the tool is scoped to tabular sources and does not pretend otherwise. Teams with mixed data environments add a separate retrieval layer, which means maintaining two answer systems.
Bottom line: Pick this when your support queue is full of questions whose answers are already in a spreadsheet; plan a different architecture when your knowledge base includes PDFs, ticketing exports, or any source that is not a table.
Find your fit
More options in Customer Support / Helpdesk. Compare pricing, platforms, and features side by side.
Freemium
HVAC, plumbing, electrical, roofing contractors
Paid
Australian service businesses
Repetitive customer-service queries — ‘What is the price for product P001?’, ‘Is SKU 4820 in stock?’ — have answers that already exist in a spreadsheet someone already maintains. FrontierBase is built around that fact. You upload an Excel or CSV file, or connect a Google Sheet, configure a response policy that controls tone and evidence display, and then expose a chat interface via a widget embed or a REST API call. The retrieval step combines semantic and keyword search to surface matching rows, and the answer cites those rows directly rather than generating text from model memory.
The differentiating design choice is evidence grounding at the row level. Where most RAG systems chunk documents and retrieve passages, FrontierBase treats each row as the retrieval unit and surfaces it as the answer’s source. The vendor states this is specifically designed to reduce hallucination on operational data — prices, inventory counts, policy fields — where a wrong number is worse than no answer. Conversation context carries across turns, so a follow-up question like ‘What about P002?’ does not require re-stating the original query.
The tool fits a narrow but real use case: customer-facing or internal chat where the ground truth is tabular, the data changes regularly in a spreadsheet someone already owns, and the deployment timeline needs to be short. It breaks outside that boundary. There are no connectors for relational databases, document stores, or unstructured text sources described in the vendor documentation. Teams whose knowledge base includes policy PDFs, CRM notes, or ticketing history run FrontierBase alongside a second retrieval system — or switch to a platform with broader ingestion support.
Deployment options include three widget layout modes — floating button, full-screen overlay, and an agent layout — plus a REST API for teams embedding queries into admin tools or backend workflows. Self-hosting is not available. All data processing runs through the vendor’s infrastructure, which is a relevant consideration for teams under strict data-residency requirements.
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