Swiftask transforms your Ratecard search. Ask questions in plain English and let the AI analyze your deals to provide the exact answer.
Result:
Stop wrestling with complex filters. Get to strategic insights in seconds.
AI Agents
ratecard
Connector ratecard · Secure OAuth 2.0
Traditional CRM search engines require exact keywords and tedious manual filtering. If you don't know the exact term or deal status, information remains hidden. This friction slows down your sales teams every day.
Main negative impacts:
Wasted time on queries
Sales reps spend precious time navigating lists to find specific opportunities.
Incomplete information
Strict text searches ignore context, hiding opportunities that are semantically linked but not keyword-matched.
Decision-making barriers
Inability to quickly extract cross-referenced data hinders fine-grained pipeline analysis.
Swiftask implements a semantic search layer over Ratecard. The AI understands the intent behind your question and scans your deals to extract relevant data, even without exact keyword matches.
BEFORE / AFTER
Standard CRM search
You search for a deal related to 'budget optimization' but the CRM contains 'cost reduction'. Your search yields zero results. You have to try multiple filter combinations manually.
With Swiftask + Ratecard
You simply ask: 'Which deals are about budget optimization?'. The agent analyzes your data, understands the semantic link to 'cost reduction', and instantly lists the corresponding opportunities.
1
STEP 1 : Connect Swiftask to your Ratecard instance
Enable the Ratecard connector in Swiftask to authorize secure indexing of your sales data.
2
STEP 2 : Automatic semantic indexing
The agent analyzes and vectorizes your deals to enable deep understanding of relationships between your data.
3
STEP 3 : Ask your question in natural language
Query your database as you would speak to a colleague: 'What are the current deals for the luxury sector?'.
4
STEP 4 : Leverage the results
Get structured answers with direct links to the relevant opportunities in Ratecard.
The agent analyzes deal descriptions, follow-up notes, statuses, and custom fields within Ratecard.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-ratecard@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
No need to memorize nomenclatures: ask questions naturally.
Find forgotten deals thanks to the AI's contextual understanding.
Let the AI filter the noise to present only relevant data.
Share quick and precise searches with colleagues for better collaboration.
Swiftask enhances your existing Ratecard experience without changing your input processes.
Swiftask applies enterprise-grade security standards for your ratecard automations.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
| Metric | Before | After |
|---|---|---|
| Search time | Several minutes (manual) | Under 5 seconds |
| Relevance rate | Variable (syntax dependent) | Very high (contextual) |
| User effort | High (multiple filters) | Low (natural language) |
| CRM adoption | Low (frustrating) | High (useful tool) |
Stop wrestling with complex filters. Get to strategic insights in seconds.