Marketing
Europe
3
heet.ai is an AI-powered platform designed to optimize B2B sales processes and build trusted relationships at scale. The solution helps sales and marketing teams automate LinkedIn outreach, generate contextual comments, increase visibility, and accelerate pipeline growth.
When our team took over the platform, the product was technically operational — but unreliable.
Key infrastructure components were unstable, and much of the work required manual backend intervention.
The main challenges were:
LinkedIn constantly updates its request and response structures. Even small changes could break workflows and disrupt the entire automation chain. There was no reliable monitoring or validation layer in place.
The system relied heavily on proxy providers to manage user sessions safely. Multiple providers had been tested, but proxies frequently dropped, changed IP geolocation, or failed mid-session — preventing users from completing actions.
Each user required an isolated, persistent session. Coordinating proxies, backend requests, and session continuity was fragile and error-prone.
Core workflows were executed manually. Engineers had to trigger and monitor backend jobs for client requests, resulting in daily operational overhead and limiting scalability.
At the same time, all clients were managed manually for billing purposes. Payments were processed via invoices only. There was no subscription system, no automation, and no scalable monetization logic.
Post collection ran only once every 24 hours. Users had to wait for updates. There was minimal automation for comment replies or engagement flows.
In short, the product was inconsistent, not automatic, and couldn’t scale.
Crunch-IS was engaged to:
We redesigned how the system interacts with LinkedIn.
A validation layer was introduced to automatically detect changes in API responses and prevent cascading failures. Continuous monitoring and retry logic significantly reduced system breakdowns.
After testing 5–6 providers, we selected a stable proxy partner and implemented automated proxy rotation and health checks.
If a proxy failed or changed behavior, the system replaced it automatically — without affecting the user.
This eliminated a major source of user friction.
We rebuilt session persistence to securely combine:
Each user now operates in an isolated, reliable environment — reducing login failures and unexpected session drops.
Previously, engineers manually triggered backend jobs for client requests.
We replaced this with automated pipelines:
Manual operational effort was reduced from ~2 hours daily to approximately 5 minutes of oversight.
Post aggregation frequency was improved from once every 24 hours to hourly.
This resulted in:
We transformed the business model from fully manual invoicing to a flexible SaaS structure.
The platform now supports:
This allows heet.ai to operate both as a self-service product and as a tailored solution for advanced clients — without operational overhead.
We enhanced the interface and introduced:
The platform evolved from a backend-driven to a user-driven model.
As one of the advanced AI tools for LinkedIn, heet.ai transitioned from a technically fragile tool into a scalable AI SaaS product.
The system moved from unreliable, manual processes to automated, production-ready processes.
Daily operational involvement dropped from ~2 hours to ~5 minutes.
Hourly post collection replaced once-daily updates.
Automated subscriptions unlocked scalable revenue growth, while custom packages remain supported.
The platform can now onboard and support users without backend engineering intervention.
Send an outline, a spec, or three sentences about where the system has stopped. One conversation is usually enough to know whether we’re the right fit.
Custom software, AI & ML, data and analytics, cloud, and security — from early scoping to long-term delivery.
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