Context infrastructure for AI agents
Power agents across every customer and every team.
Genloop builds your context once, adapts it to the rules, people and decisions of every customer or team, and keeps it learning.
Why now
Your data tells an agent what happened, not what to do next.
Connecting an agent to your data is the easy part. To pay the invoice or close the case, it needs your rules, who signs off, and what happened last time.
AI
Can we pay invoice 88213 today?
$41,200
920 of 1,000 units received
Data only
Rules?
Who approves?
Last time?
?
Can’t tell from the data
Data + context
Short-ship under 2% is fine
Tom approves over $25K
Credit lands in ~10 days
Pay 92%, hold 8%, send to Tom
The problem
Agent context is still built by hand, one customer at a time.
Every customer has its own systems, rules and approvers. Most of it lives in docs and people's heads, and it keeps changing.
Every customer is different
Their own systems, definitions, policies and approval chains, on top of your product.
Much of it isn’t in the data
Rules, exceptions and past decisions live in documents and people’s heads.
It keeps changing
Policies, schemas and people change. Hand-built context drifts and agents start getting it wrong.
Today
Forward-deployed engineers at every customer
Months before each customer is live
Margins eaten by services
Drifts after go-live
With Genloop
Product context built once, reused everywhere
About 3 days per new customer
Software margins on every deployment
Gets better with every use
How it works
Build your context once. Reuse it for every customer and team.
Map each new customer on top in days, or connect your own warehouse and docs and start asking in minutes. Either way, it keeps learning as agents get used.
01
Once · ~2 weeks
Capture your product
Your data model, rules and playbooks become reviewed product context.
02
Per customer · ~3 days
Activate each customer
Their systems, policies and approvers get mapped on top, inside their own environment.
03
Every day
Power the work
Your agents, any agent through MCP or API, and apps built in App Studio all use it.
04
Always on
Learn from every use
Experts approve corrections, changes get re-checked, and every agent gets sharper.
What you get
One context layer that grows with your customer base.
Every agent shares it, every customer keeps theirs private, and each new one goes live in days, not months.
Unified context
Data, documents, rules, people and decisions in one layer every agent shares, with sources on every answer.
Private by default
Runs in the customer’s cloud, on-prem or air-gapped. Each customer’s context stays isolated.
Scales across customers
Build once, reuse everywhere. Replace months of manual FDE work with days of setup.
Two ways to use it
Use it in the product you sell, or inside the company you run.
Software companies use it to put working agents into every customer. Data and business teams use the same layer for analytics and agents inside their own company.
Software companies
Put working agents into every customer, without an FDE team at each one.
Serve your product’s context to any agent the customer runs, or power your own. New customers live in days.
INTERNAL ANALYTICS
Ask anything across your warehouse, CRM and docs, and trust the answer.
Cited answers, live boards, weekly reports and agents on one shared context. Connect systems where they are and use it from Slack or Teams.
In production
Live at a Fortune 500 data infrastructure company.
Their assistant now answers in minutes what used to take analysts days, across their product and a terabyte of telemetry. It has since expanded to more business units.
30%
With Genloop
94%
Accuracy on real work questions
faster answers
lower cost per question
to go live, from 6 months
The platform
Everything agents need to do real work, in one platform.
Context, learning, apps and interfaces on one shared layer, running wherever your customers need it.
Context Intelligence
Connects data, documents, rules, people and decisions into one understanding of how the business works.
Self-Learning Loop
Experts review gaps and approve corrections. Changes get re-checked before agents rely on them.
App Studio
Build agents with guardrails, live dashboards, reports and automations on the same context.
Interfaces
Reach it from the Genloop workspace, Slack and Teams, MCP, APIs, or inside your own product.
Deploys where your customers need it.
Your cloud / VPC
On-prem
Air-gapped
Isolated per customer
From the team
What we've learned building context for agents.
Research, benchmark results and field notes from the team.
FAQs
How is Genloop different from connecting ChatGPT or Claude to our data?
We sell software. How do we use Genloop in our product?
How long does onboarding take?
What data sources can Genloop connect to?
Is each customer’s data kept separate?
How do you ensure answer reliability?
How do you handle security and access controls?
Can we deploy in our own cloud?