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The Governance Layer for
Agentic Fleets

Scale your AI workforce with runtime governance. Tasalor enforces policy, delivers strategic oversight, and generates runtime intelligence, transforming autonomous agents into reliable enterprise infrastructure.

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See Tasalor in Action

Watch how Tasalor brings visibility, control, and intelligence to your agentic operations

Oversight.

Execution Made Transparent

Turn every agent run into a traceable system of record. Replay execution end-to-end, diagnose issues instantly, and maintain full operational clarity as fleets scale.

Step-by-step execution tracing
Cross-surface telemetry
Model & Tool-level visibility

Control.

Governed Autonomy

Establish operational boundaries and enforce them across every agent. Apply guardrails in real time, surface violations instantly, and maintain continuous compliance at fleet scale.

Fleet-wide policy guardrails
Real-time violation detection
Domain, cost & behavior controls
Structured compliance tracking

Optimize.

Intelligence for Agentic Operations

Tasalor transforms runtime telemetry into operational intelligence, surfacing inefficiencies, highlighting bottlenecks, and generating recommendations to optimize performance across your fleet.

Latency & cost intelligence
Deep model & token visibility
Bottleneck & execution analysis
AI-driven optimization guidance

Oversight.

Execution Made Transparent

Turn every agent run into a traceable system of record. Replay execution end-to-end, diagnose issues instantly, and maintain full operational clarity as fleets scale.

Step-by-step execution tracing
Cross-surface telemetry
Model & Tool-level visibility

Control.

Optimize.

VendorOps Control Agent #283

StatusSuccess

Duration4.1 min

Cost$0.37

Steps63

Type:Status:View:

Step / Range	Type	Action	Status	Duration
#1	HTTP	HEAD khattaragentworkspace.blob.core.windows.net/tasalor-agents/agents/vendorops/state.json	200	0.03s
#2	STORAGE	download khattaragentworkspace/tasalor-agents		0.01s
#3	LLM	gpt-5-mini-2025-08-07azure_openai		28.2s
#4	BROWSER	goto vendor-intake-portal.vercel.app	2xx	0.656s
#5	BROWSER	fill vendor-intake-portal.vercel.app/ → "Vendor Supplies"		0.27s
#6	HTTP	GET khattaragentworkspace.blob.core.windows.net/tasalor-agents/agents/vendorops/main.py	200	0.07s
#7	STORAGE	upload khattaragentworkspace/tasalor-agents		0.01s
#8	SLACK	slack.chat.postMessagechannel: #operations	2xx	0.14s

Step #

Overview

Sequence#7

TypeSTORAGE

Tool Nameupload

TransportSuccess

Duration8ms

Storage Details

OperationUPLOAD

Accountkhattaragentworkspace

Containertasalor-agents

Blob Nameagents/vendorops/state.json

Size2.03 KB

Blob Typeblock

ETag"0x80E752530BA0FB3"

Last Modified2/26/2026, 5:52:52 AM

Request IDcf061251-901e-0098-370e-a7759c000000

Compliance

Monitor policy violations and agent behavior across your fleet

OVERALL STATUS

At Risk

ACTIVE VIOLATIONS

8 active

AGENTS IMPACTED

3 / 6

Active Violations

8 violations

POLICY NAME	POLICY RULE	AGENT	TOTAL RUNS ↓	LAST SEEN	SEVERITY
Cost Ceiling Exceeded	Cost per Run	Scout Research Agent	44	Feb 25, 2026, 05:15 PM	HIGH
Unauthorized Domain Access	Allowed Domains	Sentinel Risk Intelligence	4	Feb 25, 2026, 05:28 PM	HIGH
Duration Limit Exceeded	Max Duration	Scout Research Agent	43	Feb 25, 2026, 05:15 PM	MEDIUM
Step Limit Exceeded	Max Steps	Sentinel Risk Intelligence	19	Feb 25, 2026, 03:28 PM	LOW

Page 1 of 2

Sentinel Risk Intelligence: Unauthorized Domain Access

SeverityHIGH

StatusActive

Impact

Affected Runs

First Seen

Feb 25, 2026, 02:25 PM

Last Seen

Feb 25, 2026, 05:28 PM

Latest Affected Run

Run #44

Fingerprint

domain_access:raw.githubusercontent.com

Policy

All Occurrences (4)

Run	Time	Run Status
Run #44	Feb 25, 2026, 12:24 PM	success
Run #43	Feb 25, 2026, 11:23 AM	success
Run #42	Feb 25, 2026, 10:22 AM	success
Run #41	Feb 25, 2026, 09:20 AM	success

Select Run to Investigate

Run Context

Run Number

Run #44

Timestamp

Feb 25, 2026, 12:24 PM

Violations in This Run

Policy

Violation Steps (9)

Step	Surface	Observed Value
#4	http	domain: raw.githubusercontent.com
#8	http	domain: raw.githubusercontent.com
#14	http	domain: raw.githubusercontent.com
#17	http	domain: raw.githubusercontent.com

Page 1 of 3

Sentinel Risk Intelligence #69

StatusSuccess

Duration4.7 min

Cost$0.0273

Steps198

Browser component dominates runtime

OPTIMIZE

Browser usage exceeded 54.0% (4.1s) and there are 3 browser ops, indicating runtime is concentrated in browser-driven work.

Recommendation

Inspect the 8 browser operations (start by profiling steps tied to browser.agents such as step #55) and identify heavy DOM or browser network interactions to consolidate or reduce per-step work.

Execution is highly sequential

INFO

Almost all steps run in series (~96% of 198 steps, parallelism ~1.07x), so wall-clock throughput is bounded by the serial chain length.

Recommendation

Generate a dependency map to identify independent tasks; for independent units, consider extracting them into separate runs or external orchestration so they can proceed concurrently outside this serial execution path.

Single host (api.osv.dev) concentrates calls

OPTIMIZE

api.osv.dev received the majority of HTTP calls, accounting for 133 calls (74.7% of total calls), causing a concentrated external dependency.

Recommendation

Audit the 133 calls to api.osv.dev to find repeated or granular requests; consolidate multiple requests into fewer aggregated queries or combine related GET/POST% at the request level to reduce call count.

Step #55 dominates both time and cost

OPTIMIZE

Step 55 consumed a large share of wall time (16.85%) and represents 26.51% of total run cost, indicating concentrated resource usage in one step.

Recommendation

Profile step #55 to determine if its work is browser-bound, network-bound (e.g., repeated calls to api.osv.dev), or compute-bound; then split its work into smaller sequential sub-steps or refactor heavy operations with separate runs to reduce single-step dominance.

PERFORMANCE ANALYTICS

TIME BREAKDOWN BY CATEGORY

CATEGORY	COUNT	TOTAL	AVG	%
LLM	8	2.8 min	21.31s	60.6%
HTTP	178	36.3s	0.2s	13.0%
Browser	9	38.7s	4.31s	13.8%
Storage	2	48ms	0.02s	0.0%
Tools	1	817ms	0.82s	0.3%
Overhead	1	33.9s	33.91s	12.1%

LLM ANALYTICS

USAGE BY MODEL

MODEL	CALLS	INPUT	OUTPUT	REASONING	TOTAL	COST
gpt-5-mini-2025-08-07	5	6,918	5,363	6,144	18,425	$0.0247
gemini-2.5-flash	3	315	974	3,664	4,953	$0.0025

MOST EXPENSIVE CALLS (TOP 5)

SEQ	MODEL	INPUT	OUTPUT	REASONING	COST	DURATION
55	gpt-5-mini-2025-08-07	1,677	1,421	1,984	$0.0072	47.3s
56	gpt-5-mini-2025-08-07	1,416	1,441	1,280	$0.0058	30.7s
57	gpt-5-mini-2025-08-07	1,579	917	1,024	$0.0043	23.4s
2	gpt-5-mini-2025-08-07	821	775	1,024	$0.0038	22.6s
54	gpt-5-mini-2025-08-07	1,425	809	832	$0.0036	22.5s

EXTERNAL INTERACTIONS

TOP EXTERNAL CALLS

api.osv.dev

133 calls (74.3%)

api.github.com

35 calls (19.6%)

raw.githubusercontent.com

8 calls (4.5%)

blueteamworkspace.blob.core.windows.net

2 calls (1.1%)

Slack

1 calls (0.6%)

SLOWEST EXTERNAL CALLS (TOP 5)

STEP	TYPE	TARGET	DURATION
45	browser	github.com	7.5s
48	browser	github.com	6.2s
51	browser	github.com	5.7s
49	browser	github.com	5.6s
47	browser	github.com	3.7s

Unified Governance

Agent & Model Layer

LangChain

LlamaIndex

AutoGen

CrewAI

Haystack

Custom Python

OpenAI

Anthropic

Google Gemini

Azure OpenAI

Google AI Studio

Together AI

Groq

LangChain

LlamaIndex

AutoGen

CrewAI

Haystack

Custom Python

OpenAI

Anthropic

Google Gemini

Azure OpenAI

Google AI Studio

Together AI

Groq

Infrastructure Layer

Docker

Kubernetes

AWS

Azure

Google Cloud

Vercel

Serverless

Docker

Kubernetes

AWS

Azure

Google Cloud

Vercel

Serverless

Data & Tools Layer

Stripe

GitHub

Typeform

Slack

Playwright

REST API

Pinecone

Weaviate

Amazon S3

Azure Blob

Stripe

GitHub

Typeform

Slack

Playwright

REST API

Pinecone

Weaviate

Amazon S3

Azure Blob

OpenAI

LangChain

Pinecone

Stripe

Slack

Docker

Anthropic

Playwright

Azure

AWS

CrewAI

GitHub

Import. Initialize. Govern.

Wrap your agent runtime once. Tasalor automatically instruments every model call, tool invocation, and execution step, streaming structured traces to your governance layer with zero architectural changes.

Auto-instrumentation for LLMs, Browsers, Tools & HTTP clients

Structured run tracing with step-level metadata

Policy hooks & guardrails enforced at runtime

Zero refactor. Drop-in SDK integration

agent.py

import tasalor
from openai import OpenAI

tasalor.init(
    api_key="your_api_key",
    agent_name="Support Bot"
)

client = OpenAI()

@tasalor.track_run
def main(query: str):
    response = client.chat.completions.create(
        model="gpt-5",
        messages=[{"role": "user", "content": query}]
    )
    return response.choices[0].message.content

Governance Infrastructure for Agentic Systems

Scalable plans for agents in production

Join Beta

Builder

Free

For solo developers building and testing agents.

Unlimited Agents
20,000 traces / month
14-day retention
Deterministic Runtime Guardrails and Policy Enforcement
30+ Integrations (cross-surface tracking)
Runtime Intelligence & Analytics
Email Support

Production

$500/month

For teams shipping agents to production.

Unlimited Agents
150,000 traces / month
30-day retention
Tasalor Agent API
Custom Runtime Guardrails & Policy Enforcement
30+ Integrations + Custom On-Demand Integrations
Runtime Intelligence & Analytics
Priority Support

Enterprise

Custom

For organizations with advanced requirements.

Unlimited Agents
Unlimited Traces
Custom Retention
Tasalor Agent API
Custom Guardrail & Enforcement Framework
Custom Integrations
Runtime Intelligence and Analytics
Dedicated Support
SLA Guarantee

Ready to take control?

Join leading enterprises operating production agent fleets with confidence

Join Waitlist

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The Governance Layer forAgentic Fleets

See Tasalor in Action

Oversight.

Control.

Optimize.

Oversight.

Control.

Optimize.

VendorOps Control Agent #283

Step #

Overview

Storage Details

Compliance

Active Violations

Sentinel Risk Intelligence: Unauthorized Domain Access

Impact

Fingerprint

Policy

All Occurrences (4)

Select Run to Investigate

Run Context

Policy

Violation Steps (9)

Sentinel Risk Intelligence #69

Browser component dominates runtime

Execution is highly sequential

Single host (api.osv.dev) concentrates calls

Step #55 dominates both time and cost

PERFORMANCE ANALYTICS

TIME BREAKDOWN BY CATEGORY

LLM ANALYTICS

USAGE BY MODEL

MOST EXPENSIVE CALLS (TOP 5)

EXTERNAL INTERACTIONS

TOP EXTERNAL CALLS

SLOWEST EXTERNAL CALLS (TOP 5)

Unified Governance

Import. Initialize. Govern.

Governance Infrastructure for Agentic Systems

Builder

Production

Enterprise

Ready to take control?

The Governance Layer for
Agentic Fleets