ValueStreamAI vs Port of Context

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

ValueStreamAI compared with Port of Context
Detail	ValueStreamAI	Port of Context
What it does	AI automation company delivering measurable ROI without enterprise prices	Context layer platform for regulated industries
Stage	Startup	Not given
Founded	2025	Not given
Based in	US	Not given
Pricing model	Paid	Freemium
Pricing	Pilots: $5,000–$15,000 fixed-price per workflow. Retainers: from $1,500/month for up to 15 people, $2,500–$3,000/month for 15–50 people, from $7,000/month for 50–100 people, custom pricing for 100+ people. All retainers include maintenance, model upgrades, new automations each sprint, and support at	Free: $0, includes up to 5 members, 100 context nodes, and 100 MB of indexed content. Team: $25 per seat per month (or $200 per seat billed annually), includes up to 25 members, 1,000 context nodes, and 1 GB of indexed content. Enterprise: custom pricing, includes Forward Deployed Engineers, Hybrid
Key features	AI Agent Development with OpenAI, Anthropic, and LangGraph Workflow Automation connecting CRM, billing, reporting and ops stack Fixed-price pilots with ROI verification and documentation Voice AI Development for automated phone agents Healthcare AI with HIPAA compliance and self-hosted deployment AI App Development with RAG and multi-model routing On-premises and air-gap deployment options Direct access to founder and engineering team with priority response under 4 hours Free 30-minute consultation with no obligation or sales pitch	Model-agnostic: runs on Claude, GPT, Gemini, or open-weight models Full observability: trace every tool call, retrieval, and reasoning step Isolated execution: tool calls run in isolated environments by default Code mode: reduces token usage to one-third of traditional approaches Self-hosted on your infrastructure: cloud, on-prem, or air-gapped MCP server integration: works with existing MCP servers unchanged Open source under MIT license Automatic model failover and switching
What makes it different	Measurable ROI-first approach: every engagement defined by business outcomes, not hours delivered No lock-in with month-to-month retainers and IP that transfers on day one Founder-led technical scoping ensures the quoted architecture is the architecture delivered All maintenance, model upgrades, and fixes included in one flat monthly retainer Fraction of the cost of hiring an in-house AI team while delivering results from week one	Isolated by default with no direct system access Reduces token usage to approximately one-third Runs end-to-end air-gapped with no external network calls Full transparency through open agent-observability spec (AVP) No vendor lock-in: switch models without rewriting agents
Free plan	Not given	Not given
Open source	Not given	Not given
Platforms	Not given	Not given
Public API	Not given	Not given
Community votes	0	0
DR (Domain Rating by Ahrefs)	24 −1 (down) since last check	38 no change since last check
Trust Flow (Majestic)	3	14
Citation Flow (Majestic)	28	28
Referring domains (Majestic)	105	102

5 details filled in for both companies.

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