Inigra Software House

Tag: devops

AI Customer Service & Booking Assistant for Rental Venues
Overview

We developed an AI-powered customer service and booking platform for Salonty.com, a network of rental venues for events, workshops, and business meetings. The solution uses natural language processing (NLP), speech-to-text, and calendar integrations to automate customer interactions: answering phone calls, handling reservations, managing availability, and responding to equipment-related questions.

Client
- Company: Salonty.com
- Industry: Hospitality /Short-term rental
- Scale: 20+ locations with daily inquiries, hundreds of bookings per month
- Client type: B2C marketplace platform
Challenge

Salonty.com operated a growing network of rental venues but faced significant inefficiencies in handling customer service:
- Staff spent hours daily answering repetitive phone calls and emails about availability, pricing, and equipment.
- Manual booking processes caused delays, double-bookings, and errors.
- Customer expectations for 24/7 support could not be met with human staff only.
- Scaling to new cities would have required a large and costly support team.
Solution

We designed and deployed an AI-driven virtual assistant that automates end-to-end customer interactions, seamlessly integrated into Salonty.com’s platform.
1. Conversational AI & Voice Integration
- Cloud-based speech-to-text and text-to-speech APIs to handle natural phone conversations.
- Multilingual support for Polish and English customers.
- NLP models trained to recognize rental-specific queries (availability, equipment, pricing).
1. Booking & Calendar Management
- Integration with Google Calendar & internal booking system APIs.
- Automatic reservation creation, modifications, and cancellations.
- Real-time availability checks across multiple venues.
1. Customer Service Automation
- AI answers FAQs about equipment (projectors, chairs, catering), location details, and access instructions.
- Escalation to human staff only for complex cases.
- SMS/email confirmation workflows with Twilio + SendGrid.
1. Architecture & Technology Stack
- AI & NLP: OpenAI GPT-4, Dialogflow CX
- Voice & Telephony: Twilio Voice, Google Speech-to-Text, Amazon Polly
- Backend: Node.js (Express), GraphQL API
- Database: PostgreSQL, Redis for session context
- Integrations: Google Calendar API, Salonty booking system, Twilio SMS, SendGrid
- Infrastructure: Dockerized microservices on AWS (ECS, RDS, S3), Terraform for IaC
- Security: OAuth2 authentication, HTTPS, encrypted data at rest & in transit
Results
- 70% of inquiries automated without human involvement.
- 50% reduction in booking errors, thanks to real-time calendar sync.
- 24/7 availability of customer service in two languages.
- 40% cost savings on customer support operations.
- Scalability: ready to support expansion to new cities without additional staff.
Supporting Information
- Key Technologies: OpenAI GPT-4, Dialogflow CX, Twilio, Google Speech-to-Text, Node.js, PostgreSQL.
- Security & Compliance: GDPR-ready data handling, voice call encryption, audit logging.
- Team: AI engineers, backend developers, DevOps, UX for conversational design.
Process
1. Discovery — mapped customer journeys, most frequent questions, and bottlenecks.
2. Prototype — built a proof-of-concept with Dialogflow and Twilio for one location.
3. Integration — connected AI assistant with calendars, booking APIs, and CRM.
4. Deployment — rolled out to all venues, trained AI on historical FAQs.
5. Optimization — fine-tuned NLP intents, improved fallback handling, added multilingual support.
6. Monitoring — dashboards for call volume, automation success rate, and escalation triggers.
Client Testimonial

“AI automation changed the way we run Salonty. Our customers get instant answers and can book anytime, while our staff focuses on higher-value tasks. Expanding to new locations is now faster and more efficient.”
— Kinga Obarska, Project Manager, Salonty.com
September 11, 2025
DevOps Solution for a Trading System on GCP Private Cloud
Overview

End-to-end DevOps transformation of a mission-critical trading platform. The solution migrated on-premise infrastructure to Google Cloud Platform (GCP) Private Cloud, implemented a robust CI/CD pipeline, and established a secure, compliant, and highly available environment to ensure uninterrupted trading operations.

Client
- Country of origin: Confidential (Europe-based financial institution)
- Industry: Capital markets / trading systems
- Scale: Thousands of daily transactions, high-frequency trading workloads, strict SLA and compliance requirements
- Client type: Enterprise (regulated, mission-critical system)
- Website: (confidential, NDA)
Challenge

The client’s trading system ran on aging on-premise infrastructure that no longer met performance, scalability, or compliance needs. Key issues included:
- Limited scalability to handle peak trading volumes.
- Long, risky deployment processes with downtime during releases.
- Lack of robust disaster recovery and backup strategy.
- Security risks and difficulty maintaining compliance in a dynamic regulatory environment.
- Operational inefficiencies and high infrastructure costs.
Solution

We designed and implemented a DevOps-powered cloud migration to GCP Private Cloud, ensuring modernization without disrupting ongoing trading operations:
1. Cloud Migration & Infrastructure Setup
- Lift-and-shift migration of the trading platform to GCP VPC.
- Isolated network topology with VPN tunnels and interconnects for secure connectivity.
- Compute Engine and Kubernetes Engine (GKE) clusters with autoscaling.
- Infrastructure as Code (Terraform) for reproducibility and version control.
1. CI/CD Pipeline & Automation
- Build and release pipelines using Cloud Build + Artifact Registry.
- Automated testing integrated into CI.
- Blue-green and canary deployment strategies for zero-downtime releases.
- Automated configuration management with Ansible/Terraform.
1. Monitoring & Observability
- Centralized logging, metrics, and tracing via GCP Operations Suite.
- Real-time dashboards and SLA-driven alerting.
- PagerDuty / Slack integration for on-call notifications.
1. Security & Compliance
- Strict IAM role policies with least-privilege access.
- Enforced encryption in transit (TLS) and at rest.
- Network segmentation and private service endpoints.
- Vulnerability scanning integrated into CI/CD pipeline.
1. Backup & Disaster Recovery
- Automated daily snapshots and database backups to GCS.
- Point-in-time recovery procedures tested quarterly.
- Documented failover drills for full business continuity.
1. Post-Migration Operations
- Cost optimization with autoscaling and committed use discounts.
- Continuous improvement driven by operational feedback.
- Training sessions for internal IT and trading operations teams.
Results
- 100% availability during trading hours, even during updates.
- Deployment cycle reduced from days to minutes with automated CI/CD.
- 30% lower infrastructure costs via autoscaling and optimized compute.
- Successful regulatory audits with improved compliance and security posture.
- Faster recovery with tested disaster recovery and backup processes.
Supporting Information
- Key Technologies: GCP (GCE, GKE, VPC, Cloud Build, Artifact Registry, Operations Suite), Terraform, Ansible, PagerDuty, Slack.
- Security & Compliance: TLS, IAM, GDPR, MiFID II, ISO 27001.
- Team: DevOps engineers, cloud architects, security specialists.
Process
1. Discovery & Assessment – audit of trading system requirements and SLAs.
2. Design – cloud migration plan and DevOps pipeline architecture.
3. Implementation – IaC setup, CI/CD pipeline creation, and security baselines.
4. Migration – staged migration of workloads to GCP Private Cloud.
5. Validation – testing disaster recovery, zero-downtime deployments, and performance benchmarks.
6. Handover – training internal teams and setting up continuous improvement cycle.
Client Testimonial

“The migration to GCP Private Cloud transformed how we operate our trading systems. Deployments are now seamless, our compliance posture is stronger, and we can scale effortlessly during market peaks.”
— name withheld due to NDA
September 11, 2025
Automated Cloud Patching & Compliance for a Bank
Overview

Automated cloud patching and compliance monitoring framework for a global financial institution. The solution ensures secure, compliant, and efficient management of thousands of AWS resources with zero production downtime.

Client
- Country of origin: EU-based global bank with international operations
- Industry: Financial services / banking
- Scale: Tens of thousands of employees, multi-country presence, strict regulatory environment (EU & global)
- Client type: Enterprise (regulated industry, mission-critical systems)
- Website: (confidential, NDA)
Challenge

The bank’s previous patching process was manual, slow, and prone to downtime, requiring large service windows that disrupted production. After migrating to AWS, the frequency and complexity of updates grew due to:
- Regulatory and political requirements for frequent patching,
- Strict internal security SLAs (30/60/120 days depending on severity),
- Need to patch thousands of EC2 instances plus OS, databases, and network configurations,
- Maintaining full visibility of compliance and encryption posture across AWS services.
Solution

We designed and delivered a fully automated AWS-native patching and remediation framework using AWS Systems Manager, including:
- Parallel patching of EC2 instances to minimize service windows.
- Automated updates of OS packages, middleware, and application layers.
- Enforcement of network security policies alongside patching.
- Continuous monitoring of encryption compliance:
  - EBS encryption enforced,
  - S3 SSL-only policies,
  - RDS encryption enforced,
  - CloudTrail encryption enabled.
- Real-time dashboards in CloudWatch for SLA adherence, patch compliance, and encryption status.
- Pre/post-patching audits and automated application testing to validate updates.
- Framework aligned with AWS Well-Architected best practices for security and operational excellence.
Results
- 95% faster patching cycles (days → hours).
- Zero production downtime during security updates.
- 100% compliance with internal patching SLAs (30/60/120 days).
- Improved audit readiness with continuous compliance monitoring.
- Reduced manual effort for IT staff, freeing resources for strategic projects.
Supporting Information
- Key Technologies: AWS Systems Manager, CloudWatch, CloudTrail, EC2, RDS, S3, IAM, AWS Config.
- Security & Compliance: Alignment with ISO 27001, PCI DSS, GDPR, and internal banking regulations.
- Team: Cloud architects, DevOps engineers, security specialists.
Process
1. Assessment & Discovery – review of current patching workflows and regulatory SLAs.
2. Architecture Design – AWS-native framework blueprint for automation and monitoring.
3. Implementation – Systems Manager automation documents (SSM), compliance baselines.
4. Testing – pre/post patching validation, automated app regression testing.
5. Rollout – staged rollout across dev → test → production.
6. Handover & Training – client’s IT operations team enabled to manage patching autonomously.
Client Testimonial

“With the automated patching framework, we not only reduced downtime to zero but also achieved a level of compliance that auditors immediately recognized. Our IT team can now focus on delivering new services instead of firefighting patch cycles.”
— name withheld due to NDA
September 11, 2025