Allerin Tech

Allerin is an 84-person engineering team based in Austin, Texas, founded to solve a specific problem: AI models that work in notebooks fail in production. The company focuses on shipping production-grade AI systems with KPI gates, reversible rollouts, and measurable business outcomes. It operates 16+ named AI products in live production environments—not prototypes—across security, transportation, manufacturing, retail, logistics, healthcare, and financial services. The team has 15+ years running production AI and reports an 88% client repeat rate.

Allerin works primarily with CTOs and VPs responsible for AI outcomes at startups, scale-ups, enterprises, and public agencies. The company explicitly kills projects that won't hit their KPIs; every engagement starts with measurable targets locked in writing, and pilots that can't beat baseline performance result in stopped billing. Leadership is centralized—Naveen runs enterprise deals personally, and the sales team is zero-person; everyone on the kickoff call is an engineer who built the previous deployment.

Services and capabilities

Allerin's service offerings span three broad categories: agentic AI systems, computer vision, and MLOps infrastructure. On the agentic side, the team builds multi-step reasoning agents with guardrails, policy-aligned actions, and human-in-the-loop review consoles. Deliverables include orchestration graphs in code with jailbreak/toxicity/groundedness/accuracy evaluation suites, CI/CD-enforced guardrails, and run logs with trace viewers. The GenAI Product Accelerator ships RAG features to production with vector pipelines, automated knowledge re-indexing, accuracy and hallucination gates, regression testing, and observability dashboards tracking usage and cost-per-query.

Computer vision work centers on edge-deployed detection and tracking. The Computer Vision FastTrack takes PoC to production on Jetson/x86/ARM hardware with custom model training on client footage, ONNX/TensorRT optimization, latency targets (typically 60–200ms p95), precision/recall benchmarks, and MLOps workflows with drift monitoring and retraining hooks. Named CV products include NeuroSight (sub-200ms firearm detection with behavior analytics), AllView (document intelligence), SmokeView (smoke/fire detection), and VISTA (real-time license-plate recognition with compliant audio/video redaction, CJIS-style chain-of-custody, and CAD/RMS/VMS integrations).

Platform and infrastructure services include MLOps & Model Operations (registry, drift monitoring, automated rollback, evaluation harness, CI/CD integration with GitHub Actions/GitLab CI), Platform Modernization (modular architecture, blue-green/canary deployment, observability stack with distributed tracing, API gateway, SBOM generation, SAST/DAST scanning, cost unit economics, autoscale policies), and Data & Analytics Platforms (GIS-enabled dashboards, KPI catalogs, data quality pipelines, narrative report generation with anomaly detection). The Data & Analytics Platform includes data connectors with retry logic, profiling and validation rules with alerts, and runbooks for scaling and KPI addition.

AI Security & Compliance covers prompt injection/model theft/data poisoning vulnerability analysis, LLM hardening (input validation, output filtering, jailbreak protection), RBAC and API key management, AI-specific SBOMs with model lineage and training-data provenance, and compliance mapping to SOC 2, ISO 27001, HIPAA, and NIST AI RMF with continuous monitoring and audit evidence packs.

Specialized accelerators ship in 60–90 days with KPI gates. QualiZer reduces scrap/rework via edge computer vision at manufacturing lines with explainable reviews and SKU/shift trend reporting, integrating with MES/ERP. VibraQore detects bearing and imbalance faults early using sensor and vision fusion, hooking work orders. StockVexel uses drone/AMR autonomous inventory scanning for shrink and out-of-stock visibility, reconciling to WMS. YardLytix tracks dock dwell and trailer turns via gate OCR and yard maps, integrating with TMS/YMS. ShelfSentra detects out-of-stocks and planogram drift in-aisle, pushing tasks to store devices. Queuence predicts queues and staffing alerts, tying to labor planners. Named airline solutions include SkyAide, which plugs into Amadeus, IBS Software, Comarch, or Oracle via API for dynamic award pricing via reinforcement learning, daily churn risk scoring with survival analysis, and real-time fraud detection.

Allerin also offers Product Pods: dedicated engineering teams with fractional leadership shipping code weekly. Sprints include demos with stakeholder feedback, bi-weekly retrospectives, monthly roadmap health reviews, and real-time backlog visibility with incident response SLOs. Engagement models include fixed-price Outcome Sprints, dedicated pods, and staff augmentation.

Notable work

Public case studies document measurable outcomes from live deployments. One pharma client deployed real-time IoT monitoring across 340 facilities handling 3.5M telemetry pings per hour, FDA 21 CFR Part 11 compliant, on Rails/MQTT/TimescaleDB infrastructure. A shipping logistics client built a PyTorch graph neural network optimizing routes across Atlantic, Pacific, and Indian Ocean trade lanes, generating $18M annual fuel savings across 450 vessels, still running after 6 years on PyTorch/Rails/SageMaker/SAP. A financial client deployed TensorFlow anomaly detection across 12M receipts, catching $14.7M in fraud with false positives reduced by 85%, eliminating 60K audit hours; the model retrains weekly on analyst feedback. A top-10 telehealth provider migrated from Rails 3 to Rails 7 (450K lines of code, zero downtime) over 14 months with 15,000 daily clinical users unaffected, on Rails/PostgreSQL/AWS/HIPAA.

Clients named on the website include General Electric, Novell, Liberty Mutual, FedEx, PACCAR, Johnson & Johnson, McKesson, Allstate, Albertsons, J.B. Hunt, Chevron, CBRE Group, Warner Bros, Clean Harbors, CarMax, and Vulcan Materials. The company reports outcome improvements across deployments: latency reduced 30–60% (p95), critical CVEs reduced to zero before go-live, and infrastructure spend reduced 20–40%.

How they work

Engagements begin with a 2-week discovery phase assessing business objectives, data/infrastructure readiness, and high-impact opportunities. Allerin commits to first measurable value in 4–8 weeks, with rollback capability in under 10 minutes. The company uses KPI gates at every milestone and reversible rollouts as standard. Structured intake includes a discovery call, architecture assessment, and ROI estimation. Weekly sprint demos, bi-weekly retrospectives, and monthly roadmap reviews provide transparency. The team operates on a Continuous Delivery model with dual-run infrastructure supporting blue-green/canary deployments. Security baseline includes SBOM generation, SAST/DAST scanning, CSP/HSTS headers, and secret rotation via KMS. Post-launch hypercare typically runs 2–4 weeks with SLO monitoring. Pricing is not explicitly stated on the public website.

Team and credentials

Allerin has 84 senior engineers, zero salespeople, with a single executive (Naveen) running enterprise deals. The company is headquartered in Austin, Texas (1417 S. 1st St, Austin, TX 78704). Key partnerships include AWS (cloud and edge deployment), Microsoft Azure (enterprise AI and cognitive services), NVIDIA (Jetson edge inference), and Databricks (data engineering and ML pipelines). The company reports 16+ products in production, 88% client repeat rate, and 15+ years of production AI experience. While specific certifications (SOC 2, ISO 27001, HIPAA, NIST AI RMF) are mentioned as part of service offerings, no third-party rating (Clutch, G2) or partner badges are detailed in the source material.