How the Service Works

Pricing & Billing

We do not have subscriptions or hidden fees. You pay only for results.

  • Fixed Price: Every successful purchase costs the current_price.
  • No Result = No Charge: If we find nothing, your balance remains exactly the same.
  • Safe Requests: action=search_... and action=account_... are FREE.
  • Paid Requests: Only action=buy_... deducts money.
The "Preview Quota" System

The service is primarily designed for finding and buying data. The preview_quota limits free searches to ensure fair usage.

How it works:

  • Your quota depends on your total deposit — the more you’ve deposited, the higher your quota.
  • Each search request (search_rawdata, search_people, search_filter) reduces your quota by 1.
  • If your preview_quota reaches 0, you must either wait for older searches to expire or make a purchase.

How to restore your quota?

  • Automatic reset (free): Any purchase (buy_rawdata or buy_people) instantly restores your quota to the base level.
  • Do I need to buy quota? No — not if you regularly purchase data.
  • Parsing or scraping only: Use action=buy_preview_quota only if you use the account exclusively for searching without buying data.

Data Formats

Type Format Rules Example Value
phone International E164. Digits only. No '+'. 12013427656
email Full valid email address. alex543@miller.com
username Alphanumeric. No spaces. alex654
full_name First and Last name. Latin/Cyrillic. Alex Miller
last_name Last name only. Miller
address Street and Zip code. US Only. 54 Elm St 34532
zip 5 digits. US Only. 32954
vin 17 characters. US Only. 4M2CN8H72AKJ00549
ssn 9 digits. US Only. 435655643


API Endpoints Reference

action = account_info

Get your balance, current price, wallet addresses, and preview quota.

action = check_payment

Force a system check for delayed crypto deposits.

action = search_rawdata

Searches all available databases for matching records. Returns raw data rows with all original columns from each source. Each row is a separate JSON object. The maximum number of results is limited based on your total deposit history.

  • Required: type, value
action = search_people

Searches databases where data is grouped by individual people. If matches are found, returns all available information for each matching person. Each person is represented as a separate JSON object. The maximum number of results depends on your total deposit history.

  • Required: type, value
action = search_filter

Searches the same person-level databases as search_people , but uses filters instead of exact value matches. Returns all people who match your selected criteria (e.g., country, age range, gender, or interests). Each matching person is returned as a separate JSON object with all available data. The maximum number of results depends on your total deposit history.

Required Parameter:

  • country — US, GB, DE, RU, IT, ES, BR, PT, FR

Optional Parameters:

  • related — paypal, amazon, facebook, twitter, travel, crypto, dating
  • dob_start / dob_end — 1920-2010
  • gender — M, F

action = buy_rawdata

Purchases all raw data records that match your query — the same full JSON response you’d get from search_rawdata . Returns matching rows from all databases, with each row as a separate JSON object. The maximum number of results is limited based on your total deposit history.

Tip: You can skip search_rawdata and call buy_rawdata directly — it’s safe and cost-effective.

Cost: You are charged current_price only if at least one record is found. If no data exists for your query, no money is deducted.

  • Required: type, value
action = buy_people

Purchases a single, complete person profile from the specified database. Each profile is uniquely identified by two parameters: db_name and code .

The structure and number of fields in the profile are exactly the same as what you see in the search results, so you can evaluate the data before purchasing.

⚠️ Important: Only db_name and code from search_people or search_filter results can be used for buy_people . The db_name format for people profiles always follows the country_data pattern (e.g., us_data , fr_data , de_data ). Values from search_rawdata use a different database structure and cannot be used with buy_people .

Cost: You are charged current_price only if the profile exists and is successfully retrieved. If the record is invalid or not found, no money is deducted.

  • Required: db_name, code (Get these from search results)
action = buy_preview_quota

If you’ve exhausted your daily search quota ( preview_quota = 0), this action instantly resets it to your base level.

This is useful if you use the service primarily for data analysis or information gathering — without purchasing records.

Important: You **do not need** to buy quota if you regularly purchase data. Every successful buy_people or buy_rawdata request **automatically resets** your preview quota at no extra cost.

Cost: One purchase = current_price (same as any buy request).



Live Examples

Account Info
GET / POST 

														{
  "event_result": "success",
  "event_message": "Account active",
  "username": "alex123",
  "user_balance": 41.89,
  "deposits_sum": 646.39,
  "current_price": 0.4,
  "preview_quota": 42
}
Check Payment
GET / POST 

														{"event_result":"success",
														"event_message":"No new deposits found",
														"user_balance":34.33,"deposits_sum":50.08,
														"current_price":0.45}
Search Rawdata (Full Name)
Search 

														{
    "event_result": "success",
    "event_message": "Rawdata found",
    "search_object": "Alex Miller",
    "search_type": "full_name",
    "data_mode": "rawdata",
    "row_count": 5,
    "name_count": 3,
    "email_count": 3,
    "address_count": 4,
    "phone_count": 4,
    "results": [
        {
            "db_name": "npd_2024",
            "code": "34651",
            "data": {
                "full_name": "**** ******",
                "address": "**, ********* ***, *****, ***** ****** ** **** ****",
                "county": "*********",
                "ssn9": "*******"
            }
        },
        {
            "db_name": "flytap_2022",
            "code": "90286",
            "data": {
                "full_name": "** **** ******",
                "dob": "****-**-**",
                "phone": "*************",
                "email": "*************@hotmail.com",
                "country": "**",
                "id": "********",
                "id2": "*********",
                "gender": "*",
                "reg_date": "****-**-**",
                "language": "**"
            }
        },
        {
            "db_name": "doctors_usa_2020",
            "code": "172673",
            "data": {
                "full_name": "**. **** ******** ******",
                "phone": "***********",
                "address": "**, *** *****, ****, * **** ***** **",
                "id": "**********",
                "gender": "*",
                "taxonomy_name": "********** & **********",
                "taxonomy_code": "**********",
                "credential": "*.*.",
                "npi_name": "**** ******** ******",
                "letter": "*",
                "last_update": "****-**-**",
                "enumeration_date": "****-**-**",
                "version": "*******************",
                "type_code": "*"
            }
        },
        {
            "db_name": "business_usa_2021",
            "code": "490035",
            "data": {
                "full_name": "**** ******",
                "phone": "***********",
                "email": "***********@foremost.com",
                "address": "**, ******, ****-****, * **** ***",
                "domain": "********.***",
                "company_name": "******** *********",
                "sic": "****",
                "iso_cgl": "*****",
                "sales_volume": "**** **** $***,***",
                "employees": "* ** *",
                "company_status": "*******",
                "location_type": "******",
                "company_type": "************",
                "credit_score": "*",
                "sic_name": "*********",
                "title": "******* *******",
                "naics": "******",
                "ncci": "****",
                "ca_wc": "****",
                "de_wc": "***",
                "pa_wc": "***",
                "mi_wc": "****",
                "nj_wc": "****",
                "ny_wc": "****",
                "tx_wc": "****"
            }
        },
        {
            "db_name": "acxiom_2020",
            "code": "690331",
            "data": {
                "full_name": "**** ******",
                "phone": "***********",
                "email": "**********@snet.net",
                "address": "**, ******, ****, ** ***** **",
                "ip": "***.***.***.*"
            }
        }
    ]
}
Search People (Address)
Search 

														{
    "event_result": "success",
    "event_message": "People data found",
    "row_count": 5,
    "data_mode": "people",
    "balance": 34.78,
    "current_price": 0.45,
    "result": [
        {
            "db_name": "us_data",
            "code": 185752731,
            "first_name": "Maria",
            "middle_name": "J",
            "last_name": "Burden",
            "marital": "*******",
            "gender": "F",
            "dob_year": "1957",
            "dob_month": "*",
            "dob_day": "**",
            "credit_capacity": "$****",
            "number_children": "*",
            "home_purchase_date": "****",
            "animals_pets": "*,*",
            "donor": "*,*",
            "political_affiliation_donor": "*",
            "credit_card_mail_order_buyers": "*,*,*,*,*,*,*,*",
            "investing_finance": "*,*",
            "cooking_food": "*",
            "movie_music": "*",
            "health_and_fitness": "*",
            "career_self_improvement": "*",
            "outdoor_enthusiast": "*,*,*,*",
            "last_name_rate": "*****",
            "full_name_rate": "**",
            "last_name_ethnic": "African American",
            "income": "Up to $10,000",
            "networth": "** ** $**,***",
            "address1": "**, ***** ******, *****, **** ******** ***|***_****",
            "address2": "**, *********, *****-****, **** **** * ***** **|***_**** (***_****, **_********_****, ******_****, *********_****)",
            "address2_location": "(**.******* -**.*******)",
            "address2_length_of_residence": "** ** ** *****",
            "address3": "**, *********, *****, **** **** * ***|***_****",
            "address4": "**, *******, *****, **** **** * **|***_****",
            "address5": "**, *******, *****, **** **** * ***|***_****",
            "address6": "**, ***** ****, *****-****, **** ******* ** *** *|***_****, **_********_****, ******_****",
            "address6_location": "(**.******* -**.*******)",
            "address7": "**, ***** ****, *****-****, **** ******* **|***_**** (***_****, **_********_****, ******_****, *********_****, *********_***_****)",
            "address7_location": "(**.****** -**.******)",
            "address8": "**, *********, *****-****, **** ***** **|***_**** (***_****, **_********_****, ***_*********_****, ******_****, *********_****, *********_***_****)",
            "address8_location": "(**.****** -**.******)",
            "phone1": "* (***) ***-****, **|***_****",
            "phone2": "* (***) ***-****, **|***_****, ******_**** (***_****)",
            "phone3": "* (***) ***-****, **|***_****",
            "phone4": "* (***) ***-****, **, ****|***_****",
            "phone5": "* (***) ***-****, **|***_****",
            "email1": "************@yahoo.com|********************************",
            "ssn9": "2**-**-****",
            "ssn_issued_state": "**"
        },
        {
            "db_name": "us_data",
            "code": 185749622,
            "first_name": "Donald",
            "middle_name": "W",
            "last_name": "Burden",
            "marital": "*******",
            "gender": "M",
            "dob_year": "1952",
            "dob_month": "**",
            "dob_day": "**",
            "credit_capacity": "$****",
            "number_children": "*",
            "home_purchase_date": "****",
            "animals_pets": "*,*",
            "donor": "*,*",
            "political_affiliation_donor": "*",
            "credit_card_mail_order_buyers": "*,*,*,*,*,*,*,*",
            "investing_finance": "*,*",
            "cooking_food": "*",
            "movie_music": "*",
            "health_and_fitness": "*",
            "career_self_improvement": "*",
            "outdoor_enthusiast": "*,*,*,*",
            "last_name_rate": "*****",
            "full_name_rate": "**",
            "last_name_ethnic": "African American",
            "income": "Up to $10,000",
            "networth": "$**,*** ** $***,***",
            "address1": "**, ****** *****, *****, ** ******** ***|***_****",
            "address2": "**, *********, *****-****, **** **** * ***** **|***_**** (***_****, **_********_****, ******_****, *********_****)",
            "address2_location": "(**.******* -**.*******)",
            "address2_length_of_residence": "** ** ** *****",
            "address3": "**, ***** ****, *****-****, **** ******* ** *** *|***_****, **_********_****, ******_****",
            "address3_location": "(**.******* -**.*******)",
            "address4": "**, ***** ****, *****, **** ******* **|***_****",
            "address4_location": "(**.******* -**.*******)",
            "address5": "**, ***** ****, *****-****, **** ******* **|***_****, *********_***_**** (***_****, **_********_****, ******_****, *********_****)",
            "address5_location": "(**.****** -**.******)",
            "address6": "**, *********, *****-****, **** ***** **|***_**** (***_****, **_********_****, ***_*********_****, ******_****, *********_****, *********_***_****)",
            "address6_location": "(**.****** -**.******)",
            "phone1": "* (***) ***-****, **|***_****",
            "phone2": "* (***) ***-****, **|******_**** (***_****, ***_****)",
            "phone3": "* (***) ***-****, **, ******|**_********_****, *********_***_****",
            "phone4": "* (***) ***-****, **, ****|***_****",
            "phone5": "* (***) ***-****, **|***_**** (***_****, *********_****)",
            "phone6": "* (***) ***-****, **|***_****",
            "phone7": "* (***) ***-****, **|***_**** (*********_****)",
            "email1": "**************@yahoo.com|**************************",
            "ssn9": "2**-**-****",
            "ssn_issued_state": "**"
        },
        {
            "db_name": "us_data",
            "code": 210085391,
            "first_name": "Michelle",
            "middle_name": "",
            "last_name": "Cantea",
            "marital": "*******",
            "gender": "F",
            "dob_year": "1987",
            "credit_capacity": "$****",
            "home_purchase_date": "****-**",
            "last_name_rate": "**",
            "full_name_rate": "*",
            "income": "$65,000 to $74,999",
            "networth": "$**,*** ** $***,***",
            "address1": "**, ***** ****, *****-****, **** ******* **|**_********_****, ******_**** (***_****, ***_****, *********_****, *********_***_****)",
            "address1_location": "(**.****** -**.******)",
            "phone1": "* (***) ***-****, **|**_********_****, ******_**** (***_****, ***_*********_****)"
        },
        {
            "db_name": "us_data",
            "code": 213097313,
            "first_name": "Andrew",
            "middle_name": "",
            "last_name": "Cantea",
            "marital": "*******",
            "gender": "M",
            "dob_year": "1949",
            "dob_month": "*",
            "credit_capacity": "$*****",
            "home_purchase_date": "****-**",
            "linkedin_id": "******-******-********",
            "last_name_rate": "**",
            "full_name_rate": "*",
            "income": "$65,000 to $74,999",
            "networth": "$***,*** ** $***,***",
            "address1": "**, ****** ****, *****, **** ****** ******* **|*********_**** (***_****, ***_*********_****, *********_***_****)",
            "address1_location": "(**.******* -**.*******)",
            "address2": "**, ***** ****, *****-****, **** ******* **|***_****, **_********_****, ******_**** (***_****, *********_****, *********_***_****)",
            "address2_location": "(**.****** -**.******)",
            "phone1": "* (***) ***-****, **|**_********_****, ******_**** (***_****, ***_*********_****)",
            "phone2": "* (***) ***-****, **, ******|***_**** (**_********_****, ******_****, ***_****)",
            "phone3": "* (***) ***-****, **, ******|***_**** (**_********_****, ******_****, *********_****, *********_***_****)",
            "email1": "*******@chemicomays.com|********",
            "email2": "*******@yahoo.com|********",
            "email3": "************@comcast.net|***********************************************",
            "username3": "**************|*****_****",
            "password3": "**********|*****_****",
            "ssn9": "3**-**-****",
            "ssn_issued_state": "**",
            "ssn_alt_dob": "****-*-**"
        },
        {
            "db_name": "us_data",
            "code": 56525370,
            "first_name": "Judith",
            "middle_name": "A",
            "last_name": "Graham",
            "marital": "*******",
            "gender": "F",
            "dob_year": "1946",
            "dob_month": "*",
            "dob_day": "*",
            "credit_capacity": "$*****",
            "home_purchase_date": "****-**",
            "vehicle_owned": "*",
            "animals_pets": "*",
            "family_religion_politics": "*,*,*,*,*",
            "donor": "*,*",
            "political_affiliation_donor": "*",
            "credit_card_mail_order_buyers": "*,*,*,*,*,*,*,*",
            "investing_finance": "*,*,*,*,*,**",
            "hobby_interest": "*,*,*",
            "arts_history_science": "*",
            "movie_music": "*,*,*",
            "health_and_fitness": "*,*,*",
            "collectibles_and_antiques": "*,*,*,*",
            "last_name_rate": "******",
            "full_name_rate": "***",
            "last_name_ethnic": "Scottish",
            "income": "$55,000 to $59,999",
            "networth": "$***,*** ** $***,***",
            "address1": "**, *********, *****-****, *** **** **** ***** ** **** *|**_********_****, ******_****",
            "address1_location": "(**.******* -**.*******)",
            "address1_length_of_residence": "** ***** ** ****",
            "address2": "**, *********, *****-****, *** **** **** ***** **|***_*********_**** (***_****, ***_****, **_********_****, ******_****, *********_***_****)",
            "address2_location": "(**.******* -**.*******)",
            "address3": "**, *********, *****-****, *** **** **** ***** ** **** *|***_**** (**_********_****, ******_****)",
            "address3_location": "(**.****** -**.******)",
            "address4": "**, *********, *****-****, *** **** **** ***** **|***_**** (**_********_****, ***_*********_****, *********_****, *********_***_****)",
            "address4_location": "(**.****** -**.******)",
            "address5": "**, *********, *****, *** **** **** ***** ** *|***_**** (*********_***_****)",
            "address6": "**, **** **********, *****-****, **** ********|***_**** (***_****, **_********_****, ***_*********_****, ******_****, *********_****, *********_***_****)",
            "address6_location": "(**.****** -**.******)",
            "address7": "**, ***** ****, *****-****, **** ******* **|***_**** (***_****, **_********_****, ******_****, *********_****, *********_***_****)",
            "address7_location": "(**.****** -**.******)",
            "phone1": "* (***) ***-****, **, ******|**_********_**** (*********_***_****)",
            "phone2": "* (***) ***-****, **|***_****, ******_****",
            "phone3": "* (***) ***-****, **, ******|**_********_**** (******_****)",
            "phone4": "* (***) ***-****, **, ****|***_****",
            "phone5": "* (***) ***-****, **|***_****",
            "email1": "**********@msn.com|*****************************",
            "vin1": "*****************, ****, ***, ****|***_*********_****",
            "ssn9": "1**-**-****",
            "ssn_issued_state": "**"
        }
    ]
}
Search Filter (Country, Related, Dob start, Dob end)
Search 

														{
    "event_result": "success",
    "event_message": "People data found",
    "row_count": 5,
    "data_mode": "people",
    "balance": 41.49,
    "current_price": 0.4,
    "result": [
        {
            "db_name": "de_data",
            "code": 7008,
            "first_name": "Alexandre",
            "middle_name": "",
            "last_name": "Stefano",
            "gender": "M",
            "dob_year": "1973",
            "dob_month": "**",
            "dob_day": "**",
            "phone1": "** *** *** ****|******_****",
            "email1": "***********@ig.com.br|************************",
            "password1": "********|*****_****"
        },
        {
            "db_name": "de_data",
            "code": 75520,
            "first_name": "Andreas",
            "middle_name": "",
            "last_name": "Zawadke",
            "gender": "M",
            "dob_year": "1975",
            "dob_month": "**",
            "dob_day": "*",
            "facebook_id": "**********",
            "facebook_reg_date": "****-**-**",
            "phone1": "** *** *** ****|********_****, ******_****",
            "email1": "*********@gmail.com|************************",
            "username1": "********|*****_****",
            "password1": "*******|*****_****"
        },
        {
            "db_name": "de_data",
            "code": 77863,
            "first_name": "Nuno",
            "middle_name": "",
            "last_name": "Goncalves",
            "gender": "M",
            "dob_year": "1975",
            "dob_month": "*",
            "dob_day": "**",
            "address1": "*****, *******|******_****",
            "phone1": "** *** *** ****|******_****",
            "email1": "************@hotmail.com|************************",
            "username1": "**************|*****_****",
            "password1": "*********|*****_****"
        },
        {
            "db_name": "de_data",
            "code": 102385,
            "first_name": "Dino",
            "middle_name": "",
            "last_name": "Schwager",
            "gender": "M",
            "dob_year": "1971",
            "dob_month": "*",
            "dob_day": "**",
            "phone1": "** *** *** ****|******_****",
            "email1": "************@hotmail.de|************************",
            "password1": "*********|*****_****"
        },
        {
            "db_name": "de_data",
            "code": 173521,
            "first_name": "Olaf",
            "middle_name": "",
            "last_name": "Marsson",
            "gender": "M",
            "dob_year": "1979",
            "dob_month": "*",
            "dob_day": "**",
            "phone1": "** *** *** ****|******_****",
            "email1": "***********@hotmail.com|************************",
            "username1": "******_******|*****_****",
            "password1": "*********|*****_****"
        }
    ]
}
Buy Raw Data (Full Name)
PAID 

														{
    "event_result": "success",
    "event_message": "Rawdata purchased",
    "user_balance": 34.78,
    "current_price": 0.45,
    "search_object": "Alex Miller",
    "search_type": "full_name",
    "data_mode": "rawdata",
    "row_count": 5,
    "name_count": 3,
    "email_count": 3,
    "address_count": 4,
    "phone_count": 4,
    "results": [
        {
            "db_name": "npd_2024",
            "code": "34651",
            "data": {
                "full_name": "Alex Miller",
                "address": "AK, Elmendorf Afb, 99506, 31160 Myrtle St Unit 3588",
                "county": "Anchorage",
                "ssn9": "9705165"
            }
        },
        {
            "db_name": "flytap_2022",
            "code": "90286",
            "data": {
                "full_name": "Mr Alex Miller",
                "dob": "1992-03-20",
                "phone": "5517996272403",
                "email": "alex_millerla@hotmail.com",
                "country": "BR",
                "id": "19660916",
                "id2": "434419812",
                "gender": "M",
                "reg_date": "2018-12-10",
                "language": "EN"
            }
        },
        {
            "db_name": "doctors_usa_2020",
            "code": "172673",
            "data": {
                "full_name": "Dr. Alex Sherwood Miller",
                "phone": "12036882806",
                "address": "CT, New Haven, 6511, 1 Long Wharf Dr",
                "id": "1336490648",
                "gender": "F",
                "taxonomy_name": "Obstetrics & Gynecology",
                "taxonomy_code": "207V00000X",
                "credential": "M.D.",
                "npi_name": "ALEX SHERWOOD MILLER",
                "letter": "A",
                "last_update": "2019-11-08",
                "enumeration_date": "2012-09-26",
                "version": "1690192137632612359",
                "type_code": "1"
            }
        },
        {
            "db_name": "business_usa_2021",
            "code": "490035",
            "data": {
                "full_name": "Alex Miller",
                "phone": "12013275555",
                "email": "alex.miller@foremost.com",
                "address": "NJ, Ramsey, 7446-1806, 4 Erie Plz",
                "domain": "foremost.com",
                "company_name": "FOREMOST INSURANCE",
                "sic": "6411",
                "iso_cgl": "96317",
                "sales_volume": "LESS THAN $500,000",
                "employees": "1 TO 4",
                "company_status": "PRIVATE",
                "location_type": "BRANCH",
                "company_type": "PROFESSIONAL",
                "credit_score": "C",
                "sic_name": "INSURANCE",
                "title": "Systems Analyst",
                "naics": "524291",
                "ncci": "8720",
                "ca_wc": "8720",
                "de_wc": "984",
                "pa_wc": "984",
                "mi_wc": "8720",
                "nj_wc": "8720",
                "ny_wc": "8720",
                "tx_wc": "8742"
            }
        },
        {
            "db_name": "acxiom_2020",
            "code": "690331",
            "data": {
                "full_name": "Alex Miller",
                "phone": "12036763474",
                "email": "hippybless@snet.net",
                "address": "CT, Hamden, 6514, 42 Duane Rd",
                "ip": "205.187.176.2"
            }
        }
    ]
}
Buy People
PAID 

														{
    "event_result": "success",
    "event_message": "People data purchased",
    "data_mode": "people",
    "balance": 38.29,
    "current_price": 0.4,
    "result": [
        {
            "db_name": "us_data",
            "code": 3452254,
            "first_name": "Brynda",
            "middle_name": "D",
            "last_name": "Cochran",
            "marital": "Single",
            "gender": "F",
            "dob_year": "1946",
            "dob_month": 5,
            "credit_capacity": "$5625",
            "animals_pets": "3",
            "family_religion_politics": "2,8",
            "donor": "2",
            "political_affiliation_donor": "1",
            "credit_card_mail_order_buyers": "3,4,8,9",
            "investing_finance": "9",
            "hobby_interest": "1",
            "movie_music": "2,4",
            "last_name_rate": "50591",
            "full_name_rate": "1",
            "mode": 0,
            "last_name_ethnic": "Irish",
            "income": "$30,000 to $34,999",
            "networth": "$30,001 to $100,000",
            "address1": "SC, Greer, 29651-6460, 151 Cotton Rd|us_citizens_2023, acxiom_2020",
            "address1_location": "(34.914311 -82.183816)",
            "address1_length_of_residence": "15 Years or more"
        }
    ]
}
Buy Preview Quota
PAID 

														{"event_result":"success",
														"event_message":"Preview quota successfully extended",
														"preview_quota":20,"balance":34.33,"current_price":0.45}


Error Codes Reference

  • Invalid or missing parameter... — Check your spelling.
  • No records for this data — Database is empty for this value. No money charged.

  • Rate limit, please wait... — Add a delay between requests.
  • Daily preview_quota exhausted. Wait... — Limit reached (0). Solution: Make any purchase to reset instantly.
  • Total deposit is below... minimum — Your total deposit is under $50. API is locked.

  • server error — Internal system error.
  • service unavailable — Maintenance. Try again later.