Vetorial Generative agents
AI employees that learn from your company
See how the agents work, what independent studies measured against human-only work, and where your judgment is still essential.
13
specialists ready to hire, from engineering to trading
60–70%
of work time goes to activities that generative AI and other technologies could already automate
7 days
until your agent's first progress report
How it works
From hiring to first delivery
Four steps. None of them requires coding or configuring AI.
Pick the role
Engineering, marketing, sales, finance, trading and more. Each specialist comes with its own tools, tasks and routine.
Connect your tools
GitHub, CRM, WhatsApp, spreadsheets. The agent only gets the access you grant, plus its own hardware and phone line when needed.
Ask like you would a teammate
Plain-language messages. It plans, executes and asks for your approval on anything sensitive.
It learns and improves
Every correction becomes vector memory. Each week you get a report on what it learned and what got better.
Under the hood
What's inside every agent
Vetorial Generative combines a language model, a memory that grows with use and control rules you define.
Vetorial Generative memory
Stores decisions, preferences and corrections in a vector memory and checks that history before acting.
Real tools
Uses the same software as your team, with permissions you set and access you can revoke at any time.
You stay in control
Assisted, hybrid or autonomous mode. Publishing, paying or talking to customers can always require your approval.
Measured progress
A report with completed tasks, the week's learnings and anything that still needs your review.
Data from real studies
What the studies say
Independent research compared professionals working with and without generative AI. The numbers below come from the original papers.
Software development
55.8%
faster to finish the same task
Relative time, no-AI group = 100 · lower is better
Controlled experiment: developers built the same HTTP server in JavaScript, half with an AI assistant and half without.
Customer support
+14%
issues resolved per hour
Relative result, no-AI group = 100
More than 5,000 agents tracked in a real operation. Among the least experienced, the gain reached 34%.
Professional writing
−40%
time, with 18% higher quality
Relative time, no-AI group = 100 · lower is better
453 college-educated professionals wrote everyday documents such as press releases, reports and analyses.
Strategy consulting
+40%
higher quality work
Relative result, no-AI group = 100
758 Boston Consulting Group consultants. With AI, they completed 12.2% more tasks, 25.1% faster.
Comparison
Human, agent or both?
The studies measured people working with AI, not AI alone. That's why Vetorial Generative agents are designed to add to your team.
Professional
Vetorial Generative agent
Professional + agent
Availability
Professional
A regular working week, around 40–44 h
Vetorial Generative agent
Whatever schedule you set, including nights and weekends
Professional + agent
Continuous coverage, with human review during business hours
Speed on repetitive tasks
Professional
Human pace, drops under high volume
Vetorial Generative agent
Minutes, even during demand spikes
Professional + agent
Up to 55.8% faster in programming [1]
Accuracy on well-defined tasks
Professional
Varies with fatigue and interruptions
Vetorial Generative agent
Follows the same process every time, but can be confidently wrong
Professional + agent
Over 40% higher quality in consulting [4]
Judgment in new situations
Professional
Strength: context, ethics and common sense
Vetorial Generative agent
Limited: asks for your approval before acting
Professional + agent
You decide, the agent executes
Context memory
Professional
Lives with people and in documentation
Vetorial Generative agent
Vector memory that grows every week
Professional + agent
Knowledge stays with the company
Scale
Professional
Hiring and training takes weeks
Vetorial Generative agent
More hours or more agents in the same order
Professional + agent
A lean team with a large team's capacity
Qualitative scoring by VectorGen, based on the studies cited on this page and on product rules. Numbers in brackets point to the source.
Transparency
Where AI still gets it wrong
The same studies show clear limits. Knowing where they are is what makes an agent useful rather than risky.
−19 pp
On a task outside what AI does well, consultants using AI were 19 percentage points less likely to get it right than those working without it.
19% slower
Experienced developers, working on projects they knew deeply, took 19% longer when using early-2025 AI tools.
How Vetorial Generative agents handle this
- Assisted mode by default. The agent suggests and you approve until you trust its work.
- Approval for sensitive actions. Publishing, paying, talking to customers or changing data can always go through you.
- Weekly report. You see what it learned, where it made mistakes and what was fixed.
- One specialist per role. Each agent works in its own domain, where AI has been shown to deliver the most.
THE TEAM
Pick the specialist you need
VectorGen
Ready for an agent that learns with you?
Build your agent in a few steps and send the order via WhatsApp.