Context is scattered
Across clouds, repos, chat and people's heads.
The context layer for AI
A live state of your whole stack, shared by every agent and engineer on your team.
- Any agent via MCP
- MCP
- Any AI agent
- Live context: cloud, code, chatLive context
- Cross-account reasoning
- You own your data
The problem
Your systems are scattered across a dozen tools. Your AI sees one piece at a time.
Every session starts from zero
Tomorrow you explain your stack again.
The .md files go stale
Written by hand, copied per tool, out of date.
Each agent keeps its own copy
Switch vendors and the context stays behind.
Context is the most valuable thing your team builds with AI. Right now, you don't own it.
The solution
Give every agent the same live context
A continuously refreshed map of your cloud, code, and chat, served over MCP to every AI agent you run. No per-agent wiring, no rules files to keep alive.
How it works
Connect your cloud, code and chat.
B.O.R.I.S scans your systems, builds a system graph, and serves relevant live context to any AI agent.
Connected
Coming soon
Builds system graph
Cloud unlocksCode unlocksChat unlocks
AWS
multi-account
GCP
multi-project
Kubernetes
multi-cluster
GitHub
multi-org
Slack
Sentry
Azure
GitLab
AWS
multi-account
GCP
multi-project
Kubernetes
multi-cluster
GitHub
multi-org
Slack
Sentry
Azure
GitLab
One answer across every AWS account, GCP project and cluster
Organization-wide infrastructure inventories in minutes
Root cause behind unexpected AWS spend
Trace infrastructure changes back to the commits that caused them
Real infra context for your coding agents
Anyone tags B.O.R.I.S in a thread and gets the answer
Connected
AWS
GCP
Kubernetes
GitHub
Slack
Sentry
Azure
GitLab
Cloud unlocksCode unlocksChat unlocks
AWS
GCP
Kubernetes
GitHub
Slack
Sentry
Azure
GitLab
One answer across every AWS account, GCP project and cluster
Organization-wide infrastructure inventories in minutes
Root cause behind unexpected AWS spend
Trace infrastructure changes back to the commits that caused them
Real infra context for your coding agents
Anyone tags B.O.R.I.S in a thread and gets the answer
Benefits
Every change starts from facts.
Your engineers and their AI agents work from one live picture of your stack: what's deployed, what changed, and why.
What changes for your team
- AI agents
- Start every session from scratch and guess at your infrastructureKnow your AWS, repos and Slack before the first prompt
- Team context
- Split across people, repos, wikis and threadsOne unified context every engineer and agent reads
- Getting answers
- Wait for the one person who knows, often in another time zoneAsk in Slack or from your agent and get a grounded answer
- New joiners
- Piece it together over monthsGet the full team context on day one
Ownership
Your context. Your cloud. Any agent.
Every agent reads the same layer. Switching agents is a configuration change, not a knowledge migration.
Claude CodeCursorCodex
Your own agents
Grounded coding
Coding agents write code against your real AWS, repos and conventions. No CLAUDE.md, AGENTS.md or .cursorrules to maintain.
Fewer pull requests that break in production.
Evidence-backed answers
One question pulls together a GitHub deploy, an IAM change in AWS and a Slack discussion into a single grounded answer.
Senior engineers stop answering the same "where does this live?" question.
Faster root cause
Timestamped history answers "what was true when the incident happened?" Postmortems start as a draft for the team to review.
From alert to root cause in minutes, not hours of digging across tools.
Safe access for AI to production
Agents read live production state. Anything that changes infrastructure needs explicit approval.
Less time lost to context gathering, more time shipping.
Security reviews
Find every service a CVE reaches, across all repos and accounts, in one question.
Severity based on facts, not on the rule alone.
Save time on re-explanations
Every conversation adds to shared memory, so no one explains the same system twice.
New engineers are productive in their first week, not after months of asking around.
Change history
Ask how a service is built, and what changed.
Components, dependencies and the reasoning behind design decisions, linked to the commits and tickets they came from.
- Servicecheckout
- Commita1f3c9e
- TicketPAY-214
- DecisionAdd Redis cache
Every engineer can now ask what only your seniors used to know. Onboarding takes days, not months, and seniors get back to building.
From our users
What our users say
“With B.O.R.I.S, I don't have to wait half a day for the US to wake up.”
Instead of clicking through the console, I ask: give me all the external IPs for that account, or can we do least privilege based on the logs for that service account.
More from our users
“B.O.R.I.S gave us one place to ask questions about our whole AWS estate instead of hunting for answers account by account.”
The result is faster investigations, fewer false leads, less context switching, and much lower operational overhead.
“We connected B.O.R.I.S to a coding agent so it could compare the real traffic against what the code expected, and it found the problem.”
I don't know how many weeks we'd have spent on that otherwise.
“When I hit an error, the first thing I do is ask B.O.R.I.S to collect the context.”
I'm not digging through accounts and logs anymore before I can even start thinking about the actual problem.
“We do not paste logs into anything anymore.”
It debugs issues, makes correlations no one on the team would have caught, and opens PRs with suggested fixes for review.
Security
Security and privacy by design
B.O.R.I.S runs inside your own cloud account, and sensitive data stays within your perimeter. Your data is stored on your side. Read-only by default.
Your cloud account
BAA at every tier
CloudCodeChat
B.O.R.I.SLiving map of your infrastructure
Sensitive data stays here
Read-only · MCP
Your agents and engineers
Claude CodeCursorCodex
Slack
About us
Built by engineers who lived the pain
We spent a decade building private infrastructure for HIPAA-regulated teams. Every new AI tool meant explaining it all again. So we built B.O.R.I.S.
Partners
Talk to our partner network