Source: https://ailoot.ai/models/en/pro-deepseek-ai-deepseek-r1-distill-qwen-7b/
Canonical: https://ailoot.ai/models/en/pro-deepseek-ai-deepseek-r1-distill-qwen-7b/
Language: en

# DeepSeek R1 Distill Qwen 7B

[Markdown](https://ailoot.ai/models/en/pro-deepseek-ai-deepseek-r1-distill-qwen-7b/index.md) · [JSON](https://ailoot.ai/models/en/pro-deepseek-ai-deepseek-r1-distill-qwen-7b/facts.json)

## [DeepSeek R1 Distill Qwen 7B](https://ailoot.ai/models/en/pro-deepseek-ai-deepseek-r1-distill-qwen-7b/)

DeepSeek-R1-Distill-Qwen-7B is DeepSeek’s compact dense reasoning model, fine-tuned from Qwen2.5-Math-7B using R1-generated examples. It takes text and produces text for mathematical, coding and logical tasks, with checkpoint-specific prompting guidance.

- [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`](https://ailoot.ai/models/en/pro-deepseek-ai-deepseek-r1-distill-qwen-7b/#method-0)
- [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`](https://ailoot.ai/models/en/pro-deepseek-ai-deepseek-r1-distill-qwen-7b/#method-1)

About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

Introduction: a smaller R1-derived reasoning model

DeepSeek-R1-Distill-Qwen-7B transfers reasoning examples from DeepSeek-R1 into a dense model based on Qwen2.5-Math-7B. It accepts text and generates text, including worked solutions, programming explanations and answers to logical problems. This exact 7B distillation is a separate checkpoint from full DeepSeek-R1, from the original Qwen2.5-Math-7B, and from larger distilled editions. Its name records both the reasoning-data producer and the underlying model family.

What distillation contributes

DeepSeek’s R1 research distinguishes the training of the large reasoning teacher from the fine-tuning of its smaller students. The teacher’s pipeline uses reinforcement learning and supervised stages; the released distilled models are fine-tuned with samples produced by R1. The maker describes 800,000 curated examples for these releases. Do not assume that the 7B student itself has the full model’s mixture-of-experts architecture or underwent every teacher-training stage. Distillation gives this model a learned style of reasoning; it does not make its conclusions equivalent to those of the teacher.

The exact model and its configuration

The official model table identifies Qwen2.5-Math-7B as this edition’s base. DeepSeek changes configuration and tokenizer settings, so the exact released checkpoint and chat template matter. Its published configuration uses a Qwen2 causal-language-model architecture with 28 layers and bfloat16 weights. It sets maximum positions to 131,072. That configuration value is not a separate validation of long-document accuracy: the shared R1 card’s 128K context table describes the full R1 models, while its distilled-model table identifies ancestry without publishing a per-student validated context table.

Use it for a task with a checkable outcome. For mathematics, supply the complete statement, definitions and units. For code, include the relevant function, input, observed result and desired behavior. For a logic question, list the facts and distinguish a required conclusion from an assumption. Request a final result that can be independently checked, such as a boxed value, a concise proof outline or an explained patch. These examples apply the maker’s documented reasoning scope; they are not claims that the model runs code or verifies proofs automatically.

How to prepare the prompt

DeepSeek recommends placing all instructions in the user prompt and avoiding a system prompt for this R1 release. For a mathematical problem, ask for step-by-step reasoning and a clearly delimited final answer. Include any output structure in the same prompt: for example, a short conclusion followed by assumptions and supporting calculations. An application should use the student’s own tokenizer and formatting rather than substitute the base Qwen template without checking the maker’s changes.

The maker notes that some queries can produce an empty thinking block and bypass the intended reasoning pattern. Its recommended remedy is to make generation begin with the opening thinking marker and a newline in a compatible workflow. This is a documented generation-format recommendation, not a promise that every application exposes such a control. Keep the final answer distinct from the longer reasoning text when presenting a result.

Generation settings and available space

DeepSeek recommends a temperature between 0.5 and 0.7, with 0.6 as the preferred starting point, to reduce repeated or incoherent output. Its evaluation setup uses a 32,768-token generation allowance and top\_p 0.95. Those evaluation choices are not a universal hard maximum. Reasoning, source text and the final response all need space in the configured context, so a request containing a long proof or code listing should still leave room for completion.

Limitations that affect model choice

A small distilled model remains a distinct reasoning trade-off. The maker’s release materials do not establish image, audio or video input for this checkpoint, nor a dedicated tool-calling protocol. Tool execution or access to current data would need a separately configured application workflow. The release also does not inherit later DeepSeek-R1-0528 prompt-policy changes simply through the R1 name. Verify numerical answers, inspect proposed code changes and check whether the final conclusion follows from the supplied facts; a long reasoning transcript alone is not proof of correctness.

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`

[`Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`](https://ailoot.ai/models/en/#m=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&route=Ultra&caller=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&fmt=chat)

Other /`Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`

### Overview

DeepSeek-R1-Distill-Qwen-7B is DeepSeek’s compact dense reasoning model, fine-tuned from Qwen2.5-Math-7B using R1-generated examples. It takes text and produces text for mathematical, coding and logical tasks, with checkpoint-specific prompting guidance.

Accepted inputs

Text

Results

Text

### Available in Ailoot · inputs & methods

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions`

Input types

`text`

Output types

`text`

Output format

json or SSE

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`model` | Type`string` | RequirementRequired | Values & limits Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B | Default— |
| Field`messages` | Type`message[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— |
| Field`messages[].role` | Type`string` | RequirementRequired | Values & limits Model-specific | Default— |
| Field`messages[].content` | Type`string` | RequirementOptional | Values & limits Applies when: Text conversation | Default— |
| Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse |

Input material combinations

**Text** · UTF8 text

`messages[].content`

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`content_type` | Contractapplication/json |
| Parameter`required` | Contractmodel, messages |
| Parameter`material_types` | Contracttext |
| Parameter`messages` | Contractmessage array with role/content shape |
| Parameter`file_material` | Contractactual UTF-8 document inserted as literal text; no file ID inferred |
| Parameter`optional_controls` | Contractstream |
| Parameter`control_scope` | ContractText conversation; stream is a boolean and defaults to false. |
| Parameter`output_modalities` | Contracttext |
| Parameter`hosted_operations` | Contractfalse |
| Parameter`multimodal_input_binding` | Contractnull |

Method aliases: `/chat/completions`

Lifecycle: `synchronous_or_streamed`

Send exact model ID with messages.

Context length is not an output cap.

A text file may supply literal text; image/audio/file-object inputs need exact binding.

### Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode

Not specified When fast mode is selected

Flex mode

Not specified When flex mode is selected

Maximum reasoning effort

Not specified When maximum reasoning effort uses the default adjustment

#### Ailoot rates

#### Prices by configuration

| Configuration | Rate schedule | Charge |
| --- | --- | --- |
| ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens **$0.0001** / 1K tokens Output · Output tokens **$0.0001** / 1K tokens Input · Cache read **$0** / 1K tokens Input · Cache write **$0** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

### Example requests

#### Ailoot Ultra · OpenAI Chat

curlPython SDK

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model":"Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B","messages":[{"role":"user","content":"hello"}],"stream":false}')

Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \
  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import json
from pathlib import Path
r=json.loads(Path("result.json").read_text())
for x in r.get("choices",[]):
    if x.get("message",{}).get("content"): print(x["message"]["content"])
PY_RESULT
```

```python
from openai import OpenAI
import os

if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")
client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)
result=client.chat.completions.create(model="Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B", messages=[{"role":"user","content":"hello"}], stream=False)
import base64, json
from pathlib import Path

def save_result(data, stem="result"):
    # Keep every field, including usage, IDs, reasoning and tool requests.
    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(data, ensure_ascii=False, indent=2))
    def save_blob(encoded, suffix, label):
        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)
        ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix
        file = Path(stem + "-" + label + "." + ext)
        file.write_bytes(raw)
        print("Saved", file)
    for index, block in enumerate(data.get("content") or []):
        print("Content", index, json.dumps(block, ensure_ascii=False))
    for choice in data.get("choices") or []:
        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))
    for index, item in enumerate(data.get("output") or []):
        print("Output", index, json.dumps(item, ensure_ascii=False))
        if item.get("type") == "image_generation_call" and item.get("result"):
            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))
    for ci, candidate in enumerate(data.get("candidates") or []):
        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):
            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))
            blob = part.get("inlineData") or part.get("inline_data")
            if blob and blob.get("data"):
                mime = blob.get("mimeType") or blob.get("mime_type")
                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")
                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))

save_result(result.to_dict(mode="json"))
```

### Receive and save results

#### Ailoot Ultra · OpenAI Chat

json or SSE

##### Keep all completed results

Keep every complete returned response, file and content part.

Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.

##### If the original response needs checking

Keep request/response IDs and headers. No generic text job retrieval URL is supplied.

Response fields

| Field | Type |
| --- | --- |
| Field`choices[].index` | Typeinteger |
| Field`choices[].message.content` | Typestring\|null |
| Field`choices[].message.tool_calls` | Typetool\_call\[\] |
| Field`choices[].message.reasoning_content` | Typestring |
| Field`choices[].message.reasoning_details` | Typeobject\|array |
| Field`choices[].finish_reason` | Typestring\|null |
| Field`usage` | Typeobject |

Errors and next steps

| Response | Condition | Next step |
| --- | --- | --- |
| Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |

### Aliases

#### Model aliases

**Ailoot Ultra** [`Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`](https://ailoot.ai/models/en/#m=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&route=Ultra&caller=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&fmt=chat)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`](https://ailoot.ai/models/en/#m=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&route=Ultra&caller=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&fmt=chat)

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`

[`Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`](https://ailoot.ai/models/en/#m=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&route=Ultra&caller=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&fmt=messages)

Other /`Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`

### Overview

DeepSeek-R1-Distill-Qwen-7B is DeepSeek’s compact dense reasoning model, fine-tuned from Qwen2.5-Math-7B using R1-generated examples. It takes text and produces text for mathematical, coding and logical tasks, with checkpoint-specific prompting guidance.

Accepted inputs

Text

Results

json · sse

### Available in Ailoot · inputs & methods

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages`

Input types

`text`

Output types

`json`, `sse`

Output format

JSON or SSE

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`model` | Type`string` | RequirementRequired | Values & limits Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B | Default— |
| Field`messages` | Type`message[]` | RequirementRequired | Values & limits | Default— |
| Field`messages[].role` | Type`string` | RequirementRequired | Values & limits user, assistant | Default— |
| Field`messages[].content` | Type`string` | RequirementRequired | Values & limits | Default— |
| Field`max_tokens` | Type`integer` | RequirementRequired | Values & limits | Default— |
| Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse |

Input material combinations

**Text** · UTF-8 text

`messages[].content string`

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`content_type` | Contractapplication/json |
| Parameter`required` | Contractmodel, messages, max\_tokens |
| Parameter`optional_controls` | Contractstream |
| Parameter`material_types` | Contracttext |
| Parameter`text_file_material` | ContractRead the actual UTF-8 document and put its text in the indicated input or message content string. |

Lifecycle: `synchronous_or_streamed`

### Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode

Not specified When fast mode is selected

Flex mode

Not specified When flex mode is selected

Maximum reasoning effort

Not specified When maximum reasoning effort uses the default adjustment

#### Ailoot rates

#### Prices by configuration

| Configuration | Rate schedule | Charge |
| --- | --- | --- |
| ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens **$0.0001** / 1K tokens Output · Output tokens **$0.0001** / 1K tokens Input · Cache read **$0** / 1K tokens Input · Cache write **$0** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

### Example requests

#### Ailoot Ultra · Anthropic Messages

Complete minimal JSON bodycurl · use your UTF-8 documentPython · save the complete result

```json
{
  "model": "Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
  "max_tokens": 128,
  "messages": [
    {
      "role": "user",
      "content": "Summarize the incident report."
    }
  ],
  "stream": false
}
```

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}"
export AILOOT_TEXT_FILE
python3 - <<'PY_REQUEST'
import json, os
from pathlib import Path

source_file = Path(os.environ['AILOOT_TEXT_FILE'])
if not source_file.is_file():
    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')
text = source_file.read_text(encoding='utf-8')
if not text.strip():
    raise SystemExit('Choose a document containing text')
payload = {'model': 'Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}
payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text
Path('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \
  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import json
from pathlib import Path

result = json.loads(Path('result.json').read_text(encoding='utf-8'))
print(json.dumps(result, ensure_ascii=False, indent=2))
PY_RESULT
```

```python
import json, os
from pathlib import Path

source_file = Path(os.environ['AILOOT_TEXT_FILE'])
if not source_file.is_file():
    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')
text = source_file.read_text(encoding='utf-8')
if not text.strip():
    raise SystemExit('Choose a document containing text')
payload = {'model': 'Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}
payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text
from urllib.request import Request, urlopen
from urllib.error import HTTPError

api_key = os.environ['AILOOT_API_KEY']
if not api_key.strip():
    raise SystemExit('Set AILOOT_API_KEY before making a request')
headers = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}
headers['x-api-key'] = api_key
request = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')
try:
    with urlopen(request, timeout=120) as response:
        raw = response.read()
        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')
except HTTPError as error:
    Path('result.json').write_bytes(error.read())
    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')
    raise
Path('result.json').write_bytes(raw)
import json
from pathlib import Path

result = json.loads(Path('result.json').read_text(encoding='utf-8'))
print(json.dumps(result, ensure_ascii=False, indent=2))
```

### Receive and save results

#### Ailoot Ultra · Anthropic Messages

JSON or SSE

##### Keep all completed results

Keep every complete returned response, file and content part.

Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.

##### If the original response needs checking

Keep request/response IDs and headers. No generic text job retrieval URL is supplied.

Response fields

| Field | Type |
| --- | --- |
| Field`id` | Typestring |
| Field`model` | Typestring |
| Field`content[]` | Typetext\|thinking\|tool\_use\|other content block |
| Field`stop_reason` | Typestring\|null |
| Field`usage` | Typeobject |

Errors and next steps

| Response | Condition | Next step |
| --- | --- | --- |
| Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |

### Aliases

#### Model aliases

**Ailoot Ultra** [`Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`](https://ailoot.ai/models/en/#m=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&route=Ultra&caller=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&fmt=messages)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`](https://ailoot.ai/models/en/#m=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&route=Ultra&caller=Pro%2Fdeepseek-ai%2FDeepSeek-R1-Distill-Qwen-7B&fmt=messages)

FAQ · Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B

What inputs and results are available?

`POST /v1/chat/completions` · `Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`: `text` → `text` `POST /v1/messages` · `Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`: `text` → `json`, `sse`

Which fields does the request use?

`POST /v1/chat/completions` · `Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`: `model`, `messages`, `stream` `POST /v1/messages` · `Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`: `model`, `messages`, `max_tokens`, `stream`

What limits apply?

`POST /v1/chat/completions` · `Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`: `messages.min_items`: `1`

Connect Ailoot to Claude Code, OpenCode, Hermes or your own app.

## The company and its project portfolio

The company and its project portfolio: millions of customers; monthly sales in the billions.

## Buy tokens at a discount.

Subscription discounts for regular use. Promo codes offer up to 50% off token purchases.

Subscription

Choose a discounted plan for your regular requests.

Promo code: up to 50% off

Enter your code at checkout. The price updates to reflect the current promotion.

Spending in your history

The model, tokens and amount are recorded for each request.

[Choose a subscription](https://ailoot.ai/docs/en/billing/subscriptions/) · [View model prices](https://ailoot.ai/models/en/)

## Connect the API to a product you sell.

Use Ailoot in SaaS, apps and bots under its official service offer and licence agreement. Request a reseller licence for resale.

Commercial application

Add text, image, video and audio generation to paid features in your service.

Reseller licence

Send a description of your project and how you provide access. Request written terms for use and resale.

Documents on the website

The service offer, licence agreement and data processing policy are available before you connect.

[Request a reseller licence](mailto:support@ailoot.ai) · [Service offer and licence agreement](https://ailoot.ai/legal/offer?lang=en)

## Ailoot · The company and its project portfolio





Ailoot combines established operating experience, a large client base, stable service and ongoing KPI control.





The company and its project portfolio: millions of customers; monthly sales in the billions.





Ailoot brings that operating experience to API access for AI features in customer products, agents, applications and automations.