For account managers, proposal teams, sales, and management when requirements are scattered across multiple documents.
Astrafox product · AI for sales and proposals
Assess an RFQ without manually digging through attachments
The AI agent organizes the request for quotation (RFQ) materials, compiles the requirements, and prepares an assessment for the team. The account manager reviews the result and decides whether and under what terms the company will respond. We usually deploy it as a solution on the AMODIT platform, within the process the team already uses.
We deploy the solution on Azure, Google Cloud, or AWS. We configure data sources, permissions, and connections to company systems.
Before → After
A dozen attachments no longer hold up the opportunity assessment
The agent takes over the work of reading and organizing the materials. The team starts with a prepared assessment instead of a blank page.
Before
The account manager reads a dozen attachments before identifying the requirements for the response.
After
The agent compiles the requirements from the materials and hands them to the account manager for review.
Before
The team manually organizes scattered information before it can begin assessing the RFQ.
After
The team receives organized materials and focuses on assessing the response terms.
Before
The bid decision waits until the account manager has reviewed the full set of documents.
After
The account manager verifies the prepared assessment and decides on the next step.
How the agent works
From documents to an assessment ready for review
Receives the materials
It works with the RFQ, specifications, and attachments provided in the process.
Organizes the requirements
It brings information from the documents into materials the team can review in a consistent order.
Prepares the assessment
It creates an RFQ assessment using the criteria defined during product configuration.
Hands it to the account manager
The account manager reviews the result and decides whether to bid, the scope, and the response terms.
AI recommends; a person approves.
The agent prepares materials for the decision. The designated person remains responsible for the response to the RFQ.
What the user gets
The materials needed to make an informed decision
An organized RFQ scope
Information from the RFQ, specifications, and attachments collected in one working document.
A prepared RFQ assessment
A result ready for review by the team responsible for the decision and subsequent proposal work.
A clear handoff point
The account manager receives the result, verifies it, and determines the next step in the process.
Integrations and data
The agent works within the company's environment, not alongside it
We usually deploy the agent as a solution on the AMODIT platform. The agent then becomes a step in the process: it works within the same document workflow, with the same permissions and case history, and the result reaches the right person as a task. AMODIT connects to ERP and CRM systems, data warehouses, and other company applications. When an organization does not use AMODIT, we integrate the agent directly with its systems.
RFQ sources
We select the documents and data the agent uses to prepare the assessment.
Controlled connections
We configure the interfaces and permissions required to retrieve the materials and deliver the result.
Next step in the process
We define where the reviewed result goes. The connection method depends on the interfaces available in the specific system.
Security and data
Full control over where data is processed
We deploy AI on Azure, Google Cloud, or AWS in European Union regions. The models are not trained on client data, ensuring compliance with GDPR and the AI Act.
EU regions
We select and control the data processing location within the solution architecture.
Three platforms
We have experience deploying AI on Azure, Google Cloud, including Vertex AI, and AWS.
No training on client data
The models used in the product are not trained on client data.
Minimum permissions
The agent receives only the access required to read the materials and prepare the result.
Client implementation
We start with one RFQ type and a clear decision
We configure an existing model for the client's process. We do not train LLM or OCR models.
Process and responsibility
We define who assesses the RFQ, what result is needed, and who makes the decision.
Materials and exceptions
We select the documents, criteria, incomplete cases, and situations that require manual handling.
Configuration and integrations
We select the model, instructions, permissions, and connections to company systems.
Testing and launch
We test the result on representative examples, launch the product, and monitor the quality of its work.
Related solutions
Connect RFQ assessment with subsequent proposal work
FAQ
Frequently asked questions about the RFQ agent
What does the AI Agent for RFQ Assessment do?
It organizes the RFQ materials, compiles the requirements, and prepares an assessment for the team to review. The account manager makes the decision about the response.
Does the agent decide on its own whether to bid?
No. The agent prepares an assessment. The account manager or another designated person reviews it and decides whether to bid, the scope, and the response terms.
What materials does the agent use?
It works with the RFQ, specifications, attachments, and other materials selected during process configuration.
Does the product integrate with company systems?
Yes. The agent usually operates as a solution on the AMODIT platform, which connects to ERP and CRM systems, data warehouses, and other applications. When a company does not use AMODIT, we integrate the agent directly with its systems through the available interfaces.
Where is the data processed?
We deploy AI on Azure, Google Cloud, or AWS in European Union regions. We control where the data is processed, and the models are not trained on client data.
What AI experience does Astrafox have?
One of Astrafox's owners holds a PhD in artificial intelligence and has worked with AI since 2009.
How does implementation begin?
We start with one RFQ type, its input materials, the expected result, and the person responsible for the decision. We then configure the criteria, integrations, permissions, and tests.
AI Agent for RFQ Assessment
Show us an RFQ that requires manual analysis today
Using that example, we will show how the agent organizes the requirements and prepares an assessment for the team.
See the agent work on your example