The Real-time data+AI Cloud

The Fastest path from Data to data+AI Apps.



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Delighted Global Pioneers

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Optus logo
pharmeasy logo
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Accelerate data+AI Innovation

Isima accelerates data+AI apps with easy development, a lean architecture, and fast responsiveness.


Self-serve low-code data management.
Simply use Clicks, Python, and SQL to make a use-case live in minutes.

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Hyperconverged Data Middleware.
From Pixels to Alerts, all aspects of Data Engineering are elegantly unified within bi(OS).

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p99.99 < 25ms and 5K ops/sec.
bi(OS) is industry-first in delivering consistent SLAs for ML micro-services alongside ETL.

Isima stack is fast
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1 Hour to BI, 1 Day to AI, 1 Week to API

Time-to-outcome is crucial. bi(OS) is accelerating outcomes for Global B2C pioneers. Uncover insights in hours, model actions in days, and put apps into production in weeks.

Bios - The easiest, leanest and fastest path from data to data apps.

Use Cases

bi(OS) powers B2C usecases across acquisition, personalization, fulfillment and operations.  It’s converged architecture allows a single Data Analyst to deliver outcomes in days. 

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Performance Marketing

Revenue-on-ad-spend (ROAS) is performance marketing’s Achilles heel. Read more about how bi(OS) can uplift ROAS by upto 2% by speeding up syncing 4M+ SKUs with Google Shopping, Google Ads, and Facebook ads.

TCO Optimization

First-party Analytics

Third-party SaaS “assistance” never helped and is on its way out.  Learn how bi(OS) can be used to implement first-party analytics that respect consumer privacy.

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In-session Personalization

bi(OS) converts clicks from ‘window-shoppers’ into personalized recommendations in real time.  Learn how bi(OS) helps deliver a best-in-class 6.1% CTR with 20%+ order conversion.

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Using 150 lines of code, engineers can deliver an Available-to-promise (ATP) solution that is the envy of eCommerce pioneers. Read more about how bi(OS) provides a p99 < 10ms. for ATP at Fortune 50 scale using only 4 vCPUs + 6GB RAM.

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Delivery Optimization

Utilizing customer segmentation in last-mile fulfillment is a dream for all of Retail.  Learn how bi(OS) enables a 15%+ reduction in delivery breaches that avoid 1% of GMV from cancellation.

Anomaly Detection

Anomaly Detection

bi(OS) is used to measure and correlate storage degradation, high database latencies, and business KPIs.  Learn how a single data analyst used bi(OS) to implement preemptive alerting for unified operations.

Bot detection

Bot Prevention

bi(OS) detects and merges malicious activity across the Big 3 Clouds.  These potential bot lists are available for all of Isima’s customers.  Learn how multi-cloud bot detection and prevention is implemented using bi(OS).

Build | Be Different

Thought leading insights and perspective from Isima and our customers.

Introduction What is the common infrastructure hurdle shared by high-frequency trading, ad bidding, and eCommerce? Accurate and real-time inventory. All these domains have a finite commodity to trade, and it’s constantly changing hands — every nanosecond, millisecond, or second.  If an overly accurate view of inventory is provided, the risk is lost business, and likewise, […]

Customer data is imported into bi(OS) through various mechanisms, some requiring us to expose a public HTTP endpoint. These endpoints are protected against bots. We also record these attack vectors within bi(OS). We built this multi-cloud bot detection capability in 4 weeks using this data. Further, this dynamic list of bots is also made available to all our customers.
The world’s largest eCommerce player uses zero third-party pixels. The second largest uses 20+. The second-largest player has 6X lower traffic and 2X worse conversion after 20+ years of eCommerce. Is it a coincidence?  We think not. The last decade of SaaS-based crutches to optimize the eCommerce funnel has failed. As consumers demand ever-increasing privacy, the walled gardens of Google and Apple are responding with tightening around third-party support. It's time for a new way to approach eCommerce analytics that optimizes conversions, customer experience (CX), and privacy.
Distributed systems are hard. Infrastructure SLAs, sluggish database queries, and microservices latencies must be stitched together to form an accurate view for any eCommerce business. Add agile CI/CD with a Kubernetes-esque control plane, and the fragmented observability toolchain becomes a tax. How does one answer a simple question: are the customer experience (CX) and business KPIs healthy?  Well, that’s what bi(OS) empowers eCommerce teams to do.
I am Saurabh, a Tech Lead at Pharmeasy. My team develops and maintains the ML infrastructure for serving customer recommendations. Last year, we deployed our first real-time recommendation engine for non-Rx product category recommendations on our home page.  This blog will explain how Isima’s bi(OS) helped with this initiative and the solution architecture for recommendations.