HrFlow.ai API
Agent-ready OpenAPI document · curated by JenticHR recruitingRecruiting AtsapiKey28 EndpointsREST
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For Agents
Index, parse, tag, and match candidate profiles and jobs with AI inference endpoints on the HrFlow.ai HR platform.
Use for: Parse a resume PDF and return structured candidate fields, Index a new candidate profile into the engineering source, Get a fit score between this candidate and the senior engineer job, Tag a job description with skill and seniority labels
Not supported: Does not handle payroll, employee onboarding, or interview scheduling - use for HR data parsing, indexing, tagging, embedding, and matching only.
Jentic publishes the only available OpenAPI specification for HrFlow.ai API, keeping it validated and agent-ready. The HrFlow.ai API is an AI-powered HR data platform - index profiles and jobs, parse resumes from text or files, tag and vectorize content, geocode locations, run OCR, and rate profile-job fit. It exposes 28 endpoints spanning storage (sources, boards) and inference (parsing, tagging, embedding, rating). Useful for applicant scoring, automated resume ingestion, and AI agents that augment a human-driven ATS.
Install Jentic One Beta
Connect the HrFlow.ai API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the HrFlow.ai API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fhrflow.ai%2Fhrflow" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fhrflow.ai%2Fhrflow" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with HrFlow.ai API.
Parse resumes from PDF, DOCX, or raw text into structured candidate profiles
Index profiles and jobs into a HrFlow source or board for retrieval
Generate text embeddings for semantic candidate-job matching
Tag arbitrary text with HR taxonomies (skills, seniority, function)
Score profile-to-job fit with the rating endpoint
Geocode candidate or job locations into structured coordinates
Run OCR on scanned documents to extract text before parsing
Use Cases
Patterns agents use HrFlow.ai API for, with concrete tasks.
★ Automated Resume Intake
Ingest resumes from email or career portals automatically. The agent calls POST /profile/parsing/file with the uploaded resume, then POST /profile/indexing to persist the structured profile in a HrFlow source. Replaces manual recruiter data entry and feeds downstream matching.
Parse the uploaded resume.pdf via POST /profile/parsing/file and index the resulting profile into source_key 'inbound-careers'.
Candidate-to-Job Matching
Score every active candidate against open jobs to surface a shortlist. The agent calls POST /rating with the profile and job references and returns ranked matches. For semantic discovery without explicit ratings, use POST /vectorizing/text to generate embeddings and run nearest-neighbour search against indexed profiles.
Call POST /rating with profile_key=p_123 and job_key=j_456 and return the resulting fit score and explanation.
Job Description Enrichment
Enrich job descriptions with structured tags before posting. The agent calls POST /tagging/text to extract skills, seniority, and function labels, and POST /imaging/text to generate a job illustration. Improves search discoverability on career sites.
Tag a job description via POST /tagging/text and attach the returned skill list to the indexed job record.
Resume OCR Pipeline
Process scanned PDF resumes by running them through OCR before parsing. The agent calls POST /ocr/text to extract raw text from images, then POST /parsing/text on the result, then POST /profile/indexing to persist the candidate. Captures candidates from old scanned formats that PDF parsers fail on.
Run OCR on a scanned resume image, parse the resulting text into a profile, and index the profile into source_key 'scanned-archive'.
AI Recruiting Agent via Jentic
Expose HrFlow.ai's parsing, tagging, embedding, and matching endpoints to an AI recruiter agent through Jentic. The agent searches by intent, Jentic returns the right inference endpoint, and execution happens with the API key kept in your Jentic One instance.
Search Jentic for 'parse resume', load the POST /profile/parsing/file schema, and execute against the candidate's uploaded PDF.
Key Endpoints
28 endpoints — jentic publishes the only available openapi specification for hrflow.
METHOD
PATH
DESCRIPTION
POST
/profile/parsing/file
Parse a resume PDF or DOCX into a profile
POST
/profile/indexing
Index a candidate profile into a source
POST
/job/indexing
Index a job into a board
POST
/tagging/text
Tag text with HR taxonomy labels
POST
/vectorizing/text
Generate text embeddings
POST
/rating
Score a profile against a job
POST
/ocr/text
Extract text from a scanned image
POST
/profile/parsing/file
Parse a resume PDF or DOCX into a profile
POST
/profile/indexing
Index a candidate profile into a source
POST
/job/indexing
Index a job into a board
POST
/tagging/text
Tag text with HR taxonomy labels
POST
/vectorizing/text
Generate text embeddings
POST
/rating
Score a profile against a job
POST
/ocr/text
Extract text from a scanned image
Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring HrFlow.ai by hand means sending both its X-API-KEY and X-USER-EMAIL headers on every request, keeping the api.hrflow.ai/v1 host straight across parsing and inference endpoints, and handling errors yourself. Through Jentic you install once, import the HrFlow.ai API from the API Directory, store both credentials once, and your agent calls it.
Permission scoping
HrFlow.ai takes its targets in the request body, so scope your agent to the operations it needs, such as parsing a resume file or tagging text. You choose which calls are in the allowed set, so indexing or rating operations are excluded unless you add them.
Credential isolation
Your HrFlow.ai X-API-KEY and X-USER-EMAIL values are stored once, encrypted, by your own Jentic One instance and injected at execution time. They never enter the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'parse a resume PDF' or 'vectorize this text', and Jentic returns the matching HrFlow.ai operation with its input schema so the agent calls the right endpoint without browsing the reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using HrFlow.ai API through Jentic.
Why is there no official OpenAPI spec for HrFlow.ai API?
HrFlow.ai does not publish a maintained public OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call HrFlow.ai API via structured tooling. It is validated against the live API and kept up to date. Get started with Jentic One, the self-hosted execution layer.
What authentication does the HrFlow.ai API use?
The API uses two header credentials: an API key (X-API-Key) and a user email (X-USER-EMAIL). Both are required on every call. Jentic stores them encrypted in your Jentic One instance and injects both headers at execution time.
Can I parse a resume PDF with the HrFlow.ai API?
Yes. POST /profile/parsing/file accepts a multipart upload of a resume in PDF or DOCX and returns a structured candidate profile. For raw text input, use POST /parsing/text instead. Combine with POST /profile/indexing to persist the result.
What are the rate limits for the HrFlow.ai API?
HrFlow.ai applies per-account rate limits that scale with plan tier. Inference endpoints (parsing, OCR, vectorizing) are heavier than indexing and storage calls - back off on 429 responses and batch where the endpoint supports it.
How do I score a candidate against a job with the HrFlow.ai API through Jentic?
Run pip install jentic, search for 'rate profile against job', load the POST /rating schema, and execute with the profile and job keys. Jentic returns the structured rating response with the API key handled in the vault.
Can I generate embeddings for semantic candidate search with the HrFlow.ai API?
Yes. POST /vectorizing/text returns an embedding vector for any text input. Pair it with profiles indexed via POST /profile/indexing and run nearest-neighbour search externally to surface semantically similar candidates.
Can I limit what my agent is allowed to do with the HrFlow.ai API?
Yes. Because you run Jentic One yourself, your own rules decide which HrFlow.ai operations and credentials your agent may use, and it can call only the ones you add to its allowed set. If a recruiting agent only needs to read and structure resumes, you can grant POST /profile/parsing/file and POST /tagging/text while leaving write operations like POST /profile/indexing and POST /rating out. Since HrFlow.ai takes its targets in the request body, this operation-level allow list is what controls exactly what the agent can reach.
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