The Friction: "SkillVector" vs. "API Latency"
The launch of SkillVector and the Agentic AI hiring platform pushes Edmyst to the cutting edge of HR Tech. You aren't just analyzing resumes; you are running autonomous video interviews. But for a Technical Lead, this creates a specific friction. The Friction: Your platform relies on real-time video processing and LLM inference. If you are wrapping external APIs (like OpenAI) for every interaction of the "Edy AI Coach," you introduce network latency. In a live interview, a 3-second delay between the candidate speaking and the AI responding feels like an eternity. It breaks the immersion and hurts the candidate experience.
The Risk: The "API Wrapper" Tax
You are competing with well-funded giants, yet you are bootstrapped. The Technical Risk: Scaling "Agentic AI" on external endpoints is a margin killer. As usage grows, your inference bill scales linearly (or exponentially with video tokens), eating into the profitability of every interview authorization. Furthermore, relying on external dev partners for these integrations often leaves you (the internal lead) with the "Day 2" operational burden. If the API changes or the integration breaks, you are the one debugging the production incident, not the vendor.
The Solution: 2bcloud as Your "Architecture Ops" Team
We don't replace your dev partners; we optimize what they deploy. Think of 2bcloud as the Internal Infrastructure Partner that supports Ashutosh. We handle the heavy lifting of the AWS backend, migrating generic API calls to optimized Amazon Bedrock endpoints and tuning the Kinesis Video Streams, so you can ensure the platform runs faster and cheaper than the competition.
The Economics: The "Bootstrapped" Advantage
Because Edmyst is growing efficiently (bootstrapped), unit economics are your north star. The Net Result: We help you weaponize AWS Funding. We identify specific Generative AI Innovation Funds to subsidize the cost of moving models closer to your data (on AWS). We treat your cloud bill as an engineering puzzle, optimizing it to ensure that your "Cost Per Interview" drops as you scale.
What We Handle (So You Can Focus on Stability):
Latency Optimization: We help architect the move from external API calls to Amazon Bedrock or SageMaker. By keeping the inference logic inside your AWS VPC (next to your S3 video storage), we can reduce response latency by up to 40%.
Video Pipeline Scale: "SkillVector" ingests high-def video. We optimize the Kinesis Video Streams and Transcribe pipelines to handle bursty interview schedules without choking or incurring "on-demand" pricing penalties.
Vendor Gatekeeping: You manage external code. We act as your architectural sounding board, reviewing the infrastructure choices made by partners to ensure they are scalable and secure before they hit your production environment.
Security (FTR): Enterprise HR clients (Fortune 500) demand rigorous data privacy. We run the Foundational Technical Review (FTR) to validate your architecture, giving you the "SOC 2 Ready" posture needed to close big deals.
How We Fund This Engagement (2026 Programs):
Based on Edmyst’s profile (EdTech, AI, Bootstrapped), we would target:
Generative AI Innovation Funds: Specific credits designed to support startups creating custom models on Bedrock.
AWS Activate (Scale Tier): Securing the maximum credit package to cover your growing video storage and inference spend.
Foundational Technical Review (FTR): A fully funded security audit to certify your platform for Enterprise adoption.
Proposed Next Step
I’ve drafted this based on the operational complexity of your "Agentic AI" launch and the need to optimize for latency. I’d love to verify if these performance goals match your 2026 technical roadmap.
