Prevent
- Pre-deploy risk checks
- Capacity forecasts
- Review comments before code ships, such as “this will time out under real traffic”
FreshField.ai · Runtime Intelligence
AI-powered reliability for businesses that can't afford to stop.
Runtime Intelligence watches your live systems, catches failures and security risks early and hands your team a tested fix, so problems are solved while they are still small.
FreshField.ai | AI-powered reliability for businesses that can't afford to stop
The problem
On paper vs in production.
AI writes much of our software, but it only ever sees code on paper. Code that passes locally and in lower environments still breaks in production.
Incidents are handled after the damage is done, by people reading gigabytes of logs.
1public Order checkout(Cart cart) {2 var stock = inventory.reserve(cart);3 var charge = payments.charge(cart.total());4 return orders.save(cart, stock, charge);5}
Timeout after 30 sPool exhaustedRetry storm
Break it yourself
Pick what goes wrong in production.
These eight causes only show up in running systems. Choose one to see the failure, then what Runtime Intelligence catches and the fix it would raise.
Real data is bigger and stranger than test data.
- What breaks
A customer with an unusually large order makes a query scan far more rows than any test did.
- What it noticed
query time far above normal for orders-db
- Triage decision
Real · actionable · high severity · owner: orders team
- Fix PR it would raise
Add a paginated query and an index migration, with a regression test using a large order.
From noise to signal
Gigabytes of logs are not a job for a person at 3 am.
Drag the slider to watch gigabytes of logs become the few lines that matter.
orders-service · stdoutIllustration
Raw logs: Every line, as it arrives. Dense and unreadable.
What it is
The round-the-clock engineer.
A platform that does, around the clock, every step a reliability engineer or proactive security team does, both to prevent incidents and to resolve them.
How it works
Seven stages, ending in a pull request a person merges.
Connects to the logs, metrics, traces, deploys and changes you already have. Java, C#, Python and Node.js.
Stage 1 of 7: Connect
The incident evidence pack
Everything your team needs, in one place.
Every escalated incident comes with an evidence pack. Tap a card to bring it to the front.
Everything that happened, in order, in one place.
- 02:41 New release of the orders service
- 02:58 Checkout feature switched on
- 03:02 Payment provider slowing down
- 03:04 Customers start seeing errors
The part of your product behind the problem, and the team that owns it.
- Checkout payments · payments team
- Order processing · orders team
Recent changes, ranked by how well they explain the problem.
- 1 Payment timeout shortened in release 4.12
- 2 Connection settings updated
- 3 Stock reservation clean-up
The problem reproduced safely in a test copy before any fix is proposed.
- Reproduced in a sandbox ✓
- Fix tested under the same conditions ✓
A plain-language brief for engineers, their AI assistant or management.
- What happened, who was affected and for how long
- The cause and the proposed fix
- How to stop it happening again
3 am, before and after
The same incident, two ways.
Drag the divider, tap either side, or use the arrow keys.
Evidence pack
- ✓ timeline
- ✓ where in the code
- ✓ suspect commits
- ✓ repro steps
Root cause: release 4.12 shortened the payment timeout, so connections piled up.
Proposed fix, tested and waiting for review
Waiting for human reviewdashboardlogs (1)logs (2)tracesdeploysrunbookchatstatus page
03:00:10 ERROR checkout timeout after 30000ms
03:01:21 WARN pool wait 212 active 50
03:02:32 ERROR payments 504 upstream
03:03:43 INFO GET /healthz 200
03:04:14 ERROR checkout timeout after 30000ms
03:05:25 WARN pool wait 212 active 50
03:06:30 ERROR payments 504 upstream
03:07:41 INFO GET /healthz 200
03:08:12 ERROR checkout timeout after 30000ms
03:09:23 WARN pool wait 212 active 50
03:00:34 ERROR payments 504 upstream
03:01:45 INFO GET /healthz 200
03:02:10 ERROR checkout timeout after 30000ms
03:03:21 WARN pool wait 212 active 50
03:04:32 ERROR payments 504 upstream
03:05:43 INFO GET /healthz 200
03:06:14 ERROR checkout timeout after 30000ms
03:07:25 WARN pool wait 212 active 50
03:08:30 ERROR payments 504 upstream
03:09:41 INFO GET /healthz 200
03:00:12 ERROR checkout timeout after 30000ms
03:01:23 WARN pool wait 212 active 50
03:02:34 ERROR payments 504 upstream
03:03:45 INFO GET /healthz 200
03:04:10 ERROR checkout timeout after 30000ms
03:05:21 WARN pool wait 212 active 50
03:06:32 ERROR payments 504 upstream
03:07:43 INFO GET /healthz 200
● PAGER · checkout error rate high
Acknowledge · 3:04 am
Reliability intelligence
Prevent, detect, resolve.
Detect
- Unusual behaviour spotted early
- Warnings before reliability targets slip
Resolve
- Root cause with evidence
- Approved fixes applied safely
- Proposed fixes, proven in a sandbox and tested
Security intelligence
Find the paths an attacker would take, then close them.
Finds the routes an attacker could take through your systems, explains them in plain language and proposes a fix for each. Attack tests run only in a safe copy, never on live systems.
Tap a node to see what it is and which capability found the risk.
Everything visual
See it all, not just read it.
Concept mockups of the product screens. Values shown are illustrative.
Product concepts- Service map
Service map
- Incident timeline
Incident timeline
- From incident to causecheckout timeout→Charge.csChargeAsync()connections held→Pool.javarelease()slow query→repository.pyfind_by_customer()
From incident to cause
- Attack routes
Attack routes
- Reliability targetscheckouterror budgetorderserror budgetsearcherror budget
Reliability targets
- AI action logDraft PRrelease connection on errorpendingRunbookrotate certificateapprovedCommenttimeout risk on PRposted
AI action log
Also: Ask in plain language · PDF reports for management and auditors.
Ask in plain language
Ask your production a question.
Concept preview. Answers come from preset examples with illustrative values.
Safety and trust
It proposes. People decide.
Autonomy is set per service, up to a ceiling set by the licence. Every AI action is logged with its evidence.
Autonomy level
What the platform may do
Adds root causes and suggested fixes to incidents and PR comments.
AI action logExample
Proposed: renew the payments certificate before it expires
Evidence: certificate expiry approaching · owner platform team
It proposes, people decide
It raises PRs and never merges them. Only low-risk actions, such as an approved runbook step, can be applied automatically, and only where a licence enables it.
Attacks only in a sandbox
Attack scenarios run in a sandbox or digital twin, never against live production unless the client approves.
Your source code stays with you
Your source code never leaves your environment. Personal data and secrets are masked before anything is kept.
A closed, governed product
You set policies, rules and code style through simple product screens. We run and secure everything behind them.
Deploy anywhere
SaaS or fully air-gapped.
Enterprises first, government-ready from day one.
Hosted and run by us. Nothing to install on servers.
- ✓Hosted and operated by FreshField.ai
- ✓Always up to date
- ✓Modular packages
Works with what you already run
- OpenTelemetry
- Datadog
- Splunk
- Elastic
- Cloud logs
Supported languages
- Java
- C#
- Python
- Node.js
Plans
Pay for problems solved.
Every plan includes a monthly number of solved problems, security checks and 13 months of full history. Every plan is a single seat. Plans grow with the number of solutions and services.
- Most popular
Team
For a product team running customer-facing services.
$299/ month
or $2,990 a year with a 1-year commitment
- 100 solutions a month
- Up to 20 services
- Single seat
- 14 days of instant search
- 13 months of full history
- AI applies fixes by your policy
- Email support
Start 14-day trialCard required. First charge after 14 days unless you cancel.
Business
For companies running many services with stricter security needs.
$1,499/ month
or $14,990 a year with a 1-year commitment
- 500 solutions a month
- Up to 100 services
- Single seat
- 30 days of instant search
- 13 months of full history
- AI applies fixes by your policy
- Attack testing in a safe copy of your system
- Sign in with your company account
- Priority email support
Enterprise
For banks, government and regulated industries. In our cloud or on your own servers.
Custom
Annual contract
- Solutions, limits and history to your needs
- On-premises, even fully offline
- AI runs inside your network
- Company login
- AI applies fixes by your policy
- Named contact
A solution is one problem the AI traced to its cause and resolved with a fix or a clear remedy. The same problem coming back counts once, and problems it looks into but cannot solve do not count.
Prices in US dollars per workspace, before applicable taxes. Monthly plans can be cancelled at any time. The yearly price (2 months free) requires a 1-year commitment and is billed once a year. Every plan needs a card, including Team's 14-day trial.
FAQ
Questions, answered.
No. It raises pull requests and people decide. Only low-risk actions, such as an approved runbook step, can be applied automatically, and only where your licence enables it.
How a demo works
Thirty minutes, end to end.
- 01
Pick a time
Choose a time that suits you, shown in your own time zone.
- 02
See it end to end
We walk through Runtime Intelligence from a live incident to a fix PR.
- 03
Talk about fit
We discuss how it fits your services and your deployment.
Stop incidents before they reach production.
See Runtime Intelligence on your own services, as SaaS or fully air-gapped.