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In-house AI Model Development and AWS Hosting for SaaS Product

Services Covered:

AI and Machine Learning
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Industry
Industry

Information Technology

Duration
Duration

1 month

Budget
Budget

Less than 10K

Start Date
Start Date

1 May 2025

Team Size
Team Size

1-5

Engagement Model
Engagement Model

Onshore

Project Capability Score (PCS)

gauge meter
80/100
Strong

Project Capability Score (PCS) estimates how capable fxis.ai is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

Confidential

map India

Project Summary

fxis.ai developed an in-house AI model for a B2B SaaS product to reduce operational costs while maintaining similar performance. The vendor hosted the model on Amazon Web Services within the client's expected operational cost; performance was about 90% compared to prior Amazon APIs. Deliverables were completed on or before schedule and the client highlighted the team's experience and strong work ethic.

Key Challenges

  • Ai model development

Project Deliverables

  • In-house AI model
  • Hosted model on Amazon Web Services (AWS)

Project Solution

The vendor designed and developed an in-house AI model to replace prior third-party AWS API calls, aiming to reduce operational costs without significantly degrading performance. They assigned a small team (2–5 people), built and validated the model, and deployed/hosted it efficiently on Amazon Web Services to operate within the client's expected cost envelope.

Project Outcome

  • The model was hosted efficiently on Amazon Web Services within the client's expected operational cost.
  • The in-house model's performance was about 90% of the previous Amazon API-based solution.
  • Deliverables were completed on or before the scheduled time.
  • The client praised the vendor's experience and work ethic.

Platforms

  • CloudCloud

Tech Stack

  • Amazon Web Services (AWS)Amazon Web Services (AWS)

Client Endorsement

Overall Review Rating

5star

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“fxis.ai successfully hosted the model on AWS within the client's expected operational cost. The performance was 90% as good as the previous model. fxis.ai's team delivered on or before the scheduled time and impressed the client with their experience and work ethic.”

Anonymous

CEO

Note: This endorsement is based on publicly available client feedback from external review sources.

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