AI & IT Solutions for Tech Businesses & Startups

Insecure Deployments Were Blocking Enterprise Sales

A SaaS startup was shipping code directly to production without security scanning, secrets management, or deployment audit logs. As the business moved upmarket, enterprise procurement teams were rejecting them at the security questionnaire stage. Engineering velocity was high — but trust was not.

Security-First CI/CD Pipeline, Built Into Existing Workflows

We built a security-first deployment pipeline — automated vulnerability scanning, secrets management, dependency auditing, and signed deployment logs — all integrated into their existing GitHub Actions workflow without slowing release cadence. We also produced enterprise-ready security documentation to support procurement reviews.

Measurable Improvements Within 90 Days

• Zero high-severity vulnerabilities shipped to production since implementation
• First enterprise security questionnaire passed on initial submission
• Release cadence maintained — no added deployment time
• Security posture sufficient to progress two enterprise deals previously stalled

Cloud Spend Was 3× Industry Benchmarks With No Visibility Into Why

A funded startup was burning through runway on AWS infrastructure. Oversized EC2 instances were running at under 15% utilisation, orphaned EBS volumes were accumulating costs silently, and no auto-scaling policies existed. Leadership had no cost visibility and no process for catching waste before the monthly bill arrived.

Full AWS Audit, Right-Sizing, and Automated Cost Governance

We conducted a complete audit of their AWS environment, right-sized all compute to match actual workload patterns, deleted orphaned resources, implemented auto-scaling for variable traffic, and deployed cost anomaly detection with real-time alerts to the engineering and finance teams.

Measurable Improvements Within 90 Days

• Monthly cloud spend reduced by 47% — saving over $3,800 per month
• Auto-scaling prevents both over-provisioning and traffic-related outages
• Cost anomaly alerts catch budget drift within hours, not at end of month
• Engineering team no longer managing infrastructure manually after hours

Support Tickets Were Backlogging 3–4 Days as the Team Scaled

A growing B2B platform's support team was overwhelmed with first-level queries that were answerable from existing documentation. Tickets were queuing 3 to 4 days, damaging NPS scores and threatening customer retention. Hiring more support agents wasn't economically viable at their current growth stage.

AI Support Assistant with Context-Aware Human Escalation

We integrated an AI support assistant trained on their product documentation, knowledge base, release notes, and historical ticket resolutions. The assistant resolves Tier 1 enquiries instantly and, for complex issues, escalates to human agents with a full conversation summary — eliminating the need for customers to repeat themselves.

Measurable Improvements Within 90 Days

• 58% of support tickets resolved by AI without human intervention
• Average first response time dropped from 2 days to under 2 minutes
• Human agents now focused exclusively on complex, revenue-sensitive issues
• Customer satisfaction score improved by 22 points in the following quarter