DeepImage API

Name: DeepImage API API
Brand: DeepImage API
Availability: InStock

✓ Official Vendor SpecMediaImage ProcessingapiKey2 EndpointsREST

For Agents

Submit an image for AI enhancement, upscaling, or background removal on Deep-image.ai and poll for the processed result via a job identifier.

Quickstart

Get started with DeepImage API in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"enhance an image with AI"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with DeepImage API API.

Submit an image to /rest_api/process_result with the desired enhancement options

Apply upscaling, sharpening, denoising, deblurring, and background removal in a single processing job

Poll /rest_api/result/{job_id} to retrieve the processed image URL once the job completes

Authenticate every call with the x-api-key header

GET STARTED

Start building with DeepImage API API

Explore with Jentic

View OpenAPI Document

Deep-image.ai is an AI image-editing service exposing a minimal two-endpoint API for image enhancement, upscaling, background removal, sharpening, denoising, and deblurring. Submit an image to /rest_api/process_result and the service returns a job identifier; poll /rest_api/result/{job_id} until processing finishes and the enhanced image URL is returned. Authentication is a single x-api-key header. The two-step async pattern keeps the API simple while still supporting heavy AI transforms.

Use Cases

Patterns agents use DeepImage API API for, with concrete tasks.

★ E-commerce product photo enhancement

Online stores receiving low-quality supplier images need them upscaled and cleaned before they go on the storefront. Submitting each photo to /rest_api/process_result with upscaling and background removal enabled produces a clean, transparent-background asset, and polling /rest_api/result/{job_id} recovers the processed URL when ready. The async pattern fits naturally into a queue-driven media pipeline.

POST /rest_api/process_result with the image URL and {enhance: {upscale: true}, background: {remove: true}}, then poll /rest_api/result/{job_id} every 5 seconds until status='complete'.

Restoring legacy or low-resolution photo archives

Archival projects with old, blurry, or noisy scans can run each image through Deep-image.ai with sharpening, denoising, and deblurring enabled. The single processing endpoint handles all three transforms in one job, so the workflow stays a simple submit-then-poll loop rather than chaining separate services for each step.

Submit each archived image to /rest_api/process_result with sharpen, denoise, and deblur flags, and store each returned output URL alongside the original.

Pre-print upscaling for marketing assets

Marketing teams that receive low-resolution creative from agencies often need 4x upscales for print or large-format display. /rest_api/process_result with the upscale option produces a higher-resolution output, and the polled result endpoint returns a download URL the team can pull into their asset library or DAM.

POST /rest_api/process_result with the source URL and upscale options, then poll /rest_api/result/{job_id} and store the upscaled URL in the DAM.

AI agent processing images through Jentic

An agent handling user-uploaded images can search Jentic for 'enhance an image with AI', submit each upload to Deep-image.ai without exposing the api key, and asynchronously check back via the job id. Because Jentic returns the schema for both endpoints, the agent can compose the submit-then-poll flow without studying Deep-image's docs.

Search Jentic for 'enhance an image with AI', execute /rest_api/process_result, then loop /rest_api/result/{job_id} until the job is complete.

Key Endpoints

2 endpoints — deep-image.

METHOD

PATH

DESCRIPTION

POST

/rest_api/process_result

Submit an image for AI processing and receive a job id

GET

/rest_api/result/{job_id}

Poll for the processed image once the job completes

POST

/rest_api/process_result

Submit an image for AI processing and receive a job id

GET

/rest_api/result/{job_id}

Poll for the processed image once the job completes

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

The Deep-image.ai x-api-key is stored encrypted in the Jentic vault (MAXsystem). Agents execute operations through Jentic and the header is set at call time — the raw key never enters the agent's context.

Intent-based discovery

Agents search Jentic by intent (e.g., 'enhance an image with AI' or 'remove the background from a photo') and receive the submit-and-poll pair with their input schemas, so the agent can compose the async flow without studying Deep-image's docs.

Time to first call

Direct Deep-image.ai integration: about half a day to handle the submit-and-poll pattern and the option payload. Through Jentic: under 30 minutes — search, load both schemas, execute the loop.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

remove.bg API

Specialised background-removal API with synchronous response.

Choose remove.bg when you only need background removal and prefer a single synchronous call rather than submit-and-poll.

Complementary

Cloudinary Upload API

Image storage, on-the-fly transformations, and CDN delivery.

Pair with Deep-image.ai when you want a place to store the enhanced result and serve it via a CDN with on-the-fly resizing.

Alternative

DeepAI API

Multi-model AI API including image upscaling, colorization, and background removal.

Choose DeepAI when you also need text-to-image generation or colorization beyond enhancement.

FAQs

Specific to using DeepImage API API through Jentic.

What authentication does the DeepImage API use?

Deep-image.ai uses an API key passed in the x-api-key request header on every call. Through Jentic the key is held in the encrypted vault and added to the header at execution time, so the raw key never enters the agent's context.

Can I upscale and remove the background in a single Deep-image.ai call?

Yes. POST /rest_api/process_result accepts a payload that combines enhancement options, so upscale, background removal, sharpen, denoise, and deblur can run in one job. You still need to poll /rest_api/result/{job_id} to retrieve the output URL when the job completes.

How do I get the processed image after submitting a job?

GET /rest_api/result/{job_id} with the job id returned from the submit call. Poll this endpoint until the status indicates completion, then use the output URL from the response. Build retry/backoff into your client because heavy transforms can take several seconds.

What are the rate limits for the DeepImage API?

The OpenAPI spec does not document explicit rate limits. For batch workloads, queue submissions client-side and poll only the in-flight job ids rather than holding open connections, which keeps the API key well within typical service limits.

How do I enhance an image through Jentic?

Run pip install jentic, search for 'enhance an image with AI', and Jentic returns the /rest_api/process_result operation with its input schema. Load it, supply the source URL and the enhancement flags, and execute. Then load /rest_api/result/{job_id} and poll until the job is complete.

Does Deep-image.ai accept images by direct upload or only by URL?

Per the spec, /rest_api/process_result is the single submission endpoint. Provide the image as part of the request payload as documented by Deep-image.ai. The async pattern means the API returns a job id immediately rather than waiting for processing to finish.