Kredit is the neutral risk control layer enterprises need to trust AI agents.
AI agents are becoming financial actors — spending money, calling APIs, issuing refunds. By 2028, agent-mediated B2B transactions reach $15T, with no neutral risk layer deciding what agents may do before they act. Enterprises won't deploy what they can't control.
Kredit sits between intent and execution of AI agents. Every agent gets spending limits and guardrails. Kredit checks every action in real-time and blocks the risky transactions. We develop risk control solutions so Enterprise can trust the agents.
Production is the gap.
Pilots are easy. Deployment isn't.
Enterprises have policies on paper and observability dashboards after the fact. What's missing is a runtime control layer — a place to score, throttle, or block an agent action before it commits.
Real agents. Real money. Real liability.
Every case below would have been a different headline with per-agent caps, real-time risk evaluation, and a kill switch. Each card links to the primary source.
AI coding agent wiped a production database during an explicit code freeze
Live records for 1,206 executives and 1,196 companies — gone. The agent then fabricated 4,000 fake users to mask the deletion and lied about rollback. CEO publicly called it "unacceptable and should never be possible." Logged as Incident 1152 in the AI Incidents Database.
When an AI agent acts, it does so through a tool invocation. Most enterprises have no governance here. No risk scoring before execution. No policy at the connector. No audit of what agents are actually doing.
Kredit sits between intent and execution of AI agents.
Identity tells you who the agent is. Wallets let it spend. Kredit decides what it's allowed to do — before money moves or a costly action commits.
Three commands to a working guardrail
Install, authenticate, and run a 10-agent simulation. Watch real-time block, throttle, and freeze decisions in Spend Analytics.
curl -sSL https://kredit.sh/install | sh
curl -sSL https://kredit.sh/install | sh
kredit login
kredit login
kredit demo
kredit demo
Every scenario your agents will hit in production
Accidental overspend, rogue deploys, runaway loops, anomalous calls. Kredit decides allow · throttle · block · freeze — in milliseconds.
OpenClaw
github.push_to_prod
Deploy blocked — score too low after test failures
kredit score: 380 < 400 threshold — frozen
Claude
veo.generate
Video generation blocked — budget reserved for ops
wallet balance: $12 < estimated_cost: $45
Travel Agent
flight.booking
$2,400 flight exceeds $800 max per transaction
rule: Flight cap — max_cost_per_txn: $800
Research Bot
serp_api.search
Hit 50 searches/hour rate limit
rule: Search cap — hourly_rate_limit: 50
Code Assistant
anthropic.messages
Single call cost 10× above average
anomaly detection — $47 vs $4.20 avg
Procurement Bot
aws.ec2.run
Score dropped to 340 after repeated failures
kredit score < 400 — human approval required
Content Writer
openai.chat
Wallet auto-refilled at 10% balance
priority: high — auto +50% budget
Support Agent
slack.post_message
Score dropped to 480 after outage
status: throttled — reduced limits active
Four primitives. One risk decision per action.
$ kredit check --agent=travel-bot-02 \ --action=flight.booking --cost=2400 → evaluating 3 rules… ✗ BLOCKED rule: "Flight cap" — max_cost_per_txn: $800 $ kredit check --cost=650 ✓ ALLOWED transaction_id: txn_9f2a kredit_score: 742 · active
Real-time risk control for agentic transactions
Real-time risk checks on every agent action. Block overspend, throttle abuse, and freeze rogue agents automatically. Audit all transactions and agent spending in Kredit's real-time dashboard.
11
Agents
$5,040.2
Tracked
124
Blocked
587
Avg Score
| Agent | Action | Cost | Score | Status | Reason | Latency |
|---|---|---|---|---|---|---|
| procurement-01 | meta_ads.spend | $213.53 | 780 | allowed | Within budget | 8ms |
| scraper-01 | aws.s3.get | $3.27 | 720 | allowed | Within budget | 6ms |
| task-bot-13 | sendgrid.email.send | $4.36 | 650 | blocked | Exceeds $3 per-txn limit | 9ms |
| analyst-02 | datadog.metrics | $0.81 | 510 | flagged | Score below 600 | 7ms |
| procurement-04 | meta_ads.spend | $290.75 | 540 | flagged | 10x above avg spend | 11ms |
| scraper-05 | openai.chat | $4.93 | 680 | blocked | OpenAI daily limit exceeded | 8ms |
| ad-spend-02 | google_ads.spend | $120.13 | 810 | allowed | Within budget | 5ms |
| research-bot-01 | postgres.query | $0.36 | 750 | allowed | Within budget | 4ms |
| task-bot-09 | github.api.repos | $3.43 | 380 | blocked | Score too low — frozen | 12ms |
| expense-bot-2 | venue.booking | $206.01 | 770 | allowed | Within budget | 9ms |
| task-bot-08 | openai.embeddings | $2.57 | 420 | blocked | Hourly rate limit hit | 10ms |
| ad-spend-05 | venue.booking | $106.03 | 590 | flagged | Approaching daily cap | 7ms |
Within budget
Within budget
Exceeds $3 per-txn limit
Score below 600
10x above avg spend
OpenAI daily limit exceeded
Within budget
Within budget
Score too low — frozen
Within budget
Hourly rate limit hit
Approaching daily cap
Reza governed $12T of enterprise risk.
Jacob shipped $1B ARR of enterprise AI agents.
Kredit sits at the intersection of risk and agentic AI. We've been building toward this our entire careers — and we're defining a new category: KYR, Know Your Risk. Banks got KYC. Trading got KYT. Agents need KYR.
Simple, transparent pricing.
Pay as you go, scale with your agents, or call us when you outgrow it.
Kredit Guard
Pay as you go. No monthly base.
- No monthly minimum
- Unlimited agents
- Kredit scoring
- Spending policies
- Fleet monitoring
Kredit Vault
Up to $200K/mo GMV (0.5% effective). 1% on overage.
- Unlimited agents
- Kredit scoring
- Spending policies
- Fleet monitoring
- Priority support
Kredit Enterprise
Custom base + custom overage rate.
- Everything in Vault
- On-prem deployment
- SSO / SAML
- Loss prevention guarantee
- Dedicated support
GMV = Gross Monitored Volume — the total value of agent transactions checked by Kredit.
Get your agents into production — with controls your CISO will sign off.
We'll walk through your fleet, identify the actions that need a risk decision, and stand up Kredit in a sandbox.