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Interfaze Signal Console
run nightly03
agent idle · last swept 06 Aug 2026 09:02

Companies paying to build what Interfaze already sells.

This agent watches the portfolio job boards of Y Combinator, a16z, Sequoia, Lightspeed, Bessemer and Greylock, plus a fixed universe of venture-backed companies whose business runs on documents. When one starts hiring an engineer to build OCR or structured extraction in-house, that is a company that has already decided the problem is worth money. Postings from the last week score highest, because those are the reqs nobody has called about yet. Nothing here is a guess: every point in every score traces back to a line in a live job posting.

1,221
companies watched
411
job boards found
18,879
open reqs swept
219
reqs read closely
7
leads surfaced
$0.01
cost this run

Leads worth an email

7

Ranked by how much the evidence says they are spending on this problem right now. A high score means several independent things are true at once, not that one keyword matched. Every triggering req was posted in the last two months: an evergreen posting from last year is not a buying signal, whatever it says.

72
medium
Finchfinchlegal.com
Extracting structured data from medical records and police reports for personal injury cases with human-in-the-loop verification.
via Sequoiaposted 20d ago, still listed51 staff

The req that triggered this

Member of Technical Staff, Applied AI
posted 20 days ago, still open · view posting

What they are building

The role focuses on building production-grade AI agents, structured outputs, and document-processing capabilities in-house using LLM APIs and agent frameworks.

Evidence from the posting

  • Member of Technical Staff, Applied AI
  • Build production-grade voice, browser, document, and workflow agents
  • structured outputs, and human-in-the-loop controls
  • medical records, police reports, lien management

Other open reqs that corroborate

  • Member of Technical Staff, Machine Learning
  • Legal Intake Specialist (Bilingual - English/Spanish) (manual document work)
  • Lead Paralegal (manual document work)
  • Legal Intake Specialist (manual document work)

Why it scored 72

+35Hiring to build extraction
+22Posted 1 to 3 weeks ago, still open
+15Also hiring manual reviewers

Who to approach

Viraj BindraCEO & Co-Founderlinkedin profile

How to approach them

Finch is scaling human paralegal operations alongside in-house AI agents for document processing. Interfaze provides the confidence scores and bounding boxes they need to transition from 100% manual review to exception-based routing.

Drafted outreach

confidence scores for Finch document agents
Viraj, I saw you are hiring a Member of Technical Staff, Applied AI to build document agents and structured outputs for medical records. Since you are scaling your paralegal team alongside these agents, you are likely building human-in-the-loop verification. Interfaze is an OpenAI-compatible endpoint for extraction. It returns a confidence score and bounding boxes for every field. This lets your engineers route only the uncertain fields to your paralegals, rather than having them review 100% of the document. We are not cheaper or faster than standard LLMs, but we make verification deterministic. Could we run a diff on a few of your sample medical records to show you the output?

Act on it

Drafts only, nothing is ever sent for you. Connectors light up once their keys are added to the Vercel project.
build the demo for Finch →
Nothing is generated until you ask. This reads their req and designs a document around their workflow, which costs a model call, so it happens on click.
72
medium
At-Bayat-bay.com
Extracting structured data from insurance claims and policy documents to automate underwriting and claims processing.
via Lightspeedposted 9d ago, still listed337 staff

The req that triggered this

Software Engineer (DS Team)
posted 9 days ago, still open · view posting

What they are building

The role focuses on building and maintaining machine learning systems, moving ML workloads to production, and processing unstructured data as part of a data science team.

Evidence from the posting

  • Transition ML workloads from research to production
  • shape unstructured data into a form ready for analysis
  • Software Engineer (DS Team)

Other open reqs that corroborate

  • Claims Specialist (manual document work)
  • Sr. Claims Specialist (manual document work)

Why it scored 72

+35Hiring to build extraction
+22Posted 1 to 3 weeks ago, still open
+15Also hiring manual reviewers

Who to approach

Ayelet Kutner (Shenderov)Chief Technology Officerlinkedin profile

How to approach them

At-Bay is hiring a Software Engineer for their DS Team to move ML workloads to production and handle unstructured data, while also hiring Claims Specialists. We can help them automate claims processing by providing confidence scores and bounding boxes to route only uncertain fields to human reviewers.

Drafted outreach

Unstructured data for At-Bay's DS team
Ayelet, I saw At-Bay is hiring a Software Engineer for your DS Team to transition ML workloads to production and shape unstructured data. At the same time, you are scaling your Claims Specialist team. If you are using OpenAI APIs to extract data from claims or policies, you can swap your base URL to Interfaze. Instead of raw text, we return confidence scores and bounding boxes for every extracted field. This lets your team route only low-confidence fields to your Claims Specialists, rather than reviewing every document. Could we run a diff on a few of your complex insurance documents to show you the extraction and confidence scores?

Act on it

Drafts only, nothing is ever sent for you. Connectors light up once their keys are added to the Vercel project.
build the demo for At-Bay →
Nothing is generated until you ask. This reads their req and designs a document around their workflow, which costs a model call, so it happens on click.
70
medium
Striveworksstriveworks.com
Extracting structured entities and intelligence from unstructured text and geospatial documents for national security missions.
posted 3d ago, still listed51-100 staff$33M raisedUnited States

The req that triggered this

Senior Machine Learning Engineer (Active Secret Clearance)
posted 3 days ago, still open · view posting

What they are building

The position is a Senior Machine Learning Engineer focused on developing machine learning models and analytics across various data modalities including text and unstructured data, placing it in tier 1. No third-party extraction tools are mentioned.

Evidence from the posting

  • Senior Machine Learning Engineer
  • agentic AI systems
  • custom analytics applied to image, video, text, geospatial, time series, and structured data

Other open reqs that corroborate

  • Senior Data Scientist (Active TS/SCI Clearance)
  • Senior Machine Learning Engineer (Active Secret Clearance)
  • Senior Machine Learning Engineer (Active TS/SCI Clearance)

Why it scored 70

+35Hiring to build extraction
+30Posted in the last week
+5Raised in the last 12 months

Who to approach

Craig DesjardinsCTO & Founderlinkedin profile

How to approach them

Striveworks is building agentic systems for national security where trust and drift management are paramount. Highlighting our confidence scores and bounding boxes directly aligns with their mission of providing an assurance layer for deployed models.

Drafted outreach

structured extraction for Striveworks agents
Craig, Saw you are hiring a Senior ML Engineer to build agentic systems and analytics for unstructured text and image data. If these agents need to extract structured data from documents for national security missions, trust is the bottleneck. General LLMs fail silently. We built Interfaze to solve this. It is an OpenAI-compatible endpoint for structured extraction that returns a confidence score and bounding boxes for every extracted field. Your team can route only the low-confidence fields to human reviewers, and instantly trace every value back to its exact coordinate on the page. Send over a few of your trickiest sample documents. We will run a diff and show you the confidence scores. Best, Michael

Act on it

Drafts only, nothing is ever sent for you. Connectors light up once their keys are added to the Vercel project.
build the demo for Striveworks →
Nothing is generated until you ask. This reads their req and designs a document around their workflow, which costs a model call, so it happens on click.
65
medium
Commurecommure.com
Extracting structured data from medical claims, remittance advice, and denial letters for Commure's autonomous RCM pipeline.
via Sequoiaposted 7d ago, still listed1535 staff

The req that triggered this

Software Engineer, RCM Core
posted 7 days ago, still open · view posting

What they are building

The role is a Software Engineer on the RCM AI team focusing on building autonomous backend workflows, integrations, and document extraction systems for healthcare revenue cycles, placing it in tier 2 for owning backend pipelines and data processing infrastructure.

Evidence from the posting

  • document extraction with real guardrails and compliance built in
  • Technical Operations Associate
  • Software Engineer, RCM Core

Other open reqs that corroborate

  • Staff Software Engineer, Accounts & Ledgering
  • Technical Operations Associate (manual document work)

Why it scored 65

+30Posted in the last week
+20Hiring to own the pipeline
+15Also hiring manual reviewers

Who to approach

Tanay TandonCEOlinkedin profile

How to approach them

Commure is scaling its autonomous RCM pipelines and hiring engineers for document extraction, but they still rely on manual Technical Operations Associates. Interfaze can bridge this gap by providing deterministic confidence scores and bounding boxes to route only low-confidence extractions to their human review team.

Drafted outreach

Commure RCM document extraction
Tanay, Commure is hiring an RCM Core engineer to build document extraction for claims and denials, while also hiring Technical Operations Associates to handle manual processing. The hardest part of automating RCM is verifying LLM outputs without reviewing 100% of the documents. We built Interfaze to fix this. It is an OpenAI-compatible endpoint for extraction that returns deterministic confidence scores and bounding boxes for every field. This lets you route only low-confidence fields to your Tech Ops team, leaving the rest fully automated. If you send over a few of your trickiest medical claims or remittance PDFs, I can run a diff to show you the confidence scores and bounding boxes. No call needed.

Act on it

Drafts only, nothing is ever sent for you. Connectors light up once their keys are added to the Vercel project.
build the demo for Commure →
Nothing is generated until you ask. This reads their req and designs a document around their workflow, which costs a model call, so it happens on click.
65
medium
Pivotal Healthpivotalhealth.ai
Extracting structured data from medical claims and insurance dispute documents for the Independent Dispute Resolution process.
via Bessemerposted 8d ago, still listed36 staff

The req that triggered this

Senior Applied AI/ML Engineer
posted 8 days ago, still open · view posting

What they are building

The role is a Senior Applied AI/ML Engineer responsible for designing, building, and deploying production AI systems, including LLM-powered applications, structured generation, and document intelligence workflows. It involves building machine learning solutions end-to-end rather than operating third-party software or performing manual document review.

Evidence from the posting

  • Senior Applied AI/ML Engineer
  • Build LLM-powered applications
  • structured generation

Other open reqs that corroborate

  • Staff Software Engineer, Data Engineering

Why it scored 65

+35Hiring to build extraction
+30Posted in the last week

Who to approach

No named decision maker resolved. Approach the CTO or head of engineering.

How to approach them

Pivotal Health is scaling up their AI team to automate complex IDR and reimbursement workflows. Since medical claims require absolute precision to avoid underpayment, providing deterministic extraction with confidence scores directly addresses their need to reduce human review overhead without risking accuracy.

Drafted outreach

IDR document extraction at Pivotal
Saw Pivotal is hiring a Senior Applied AI/ML Engineer to build LLM-powered applications and structured generation for your IDR platform. When extracting data from medical claims, a single misread field stalls the reimbursement. If you are building document intelligence pipelines, you likely have team members manually checking the LLM's work. Interfaze is an OpenAI-compatible endpoint for structured extraction. It returns a confidence score and bounding boxes for every extracted field. This lets you route only low-confidence fields to human reviewers, who can instantly verify them against the exact coordinates on the page. Could we run a diff on a few of your trickiest claim documents to show you the output?

Act on it

Drafts only, nothing is ever sent for you. Connectors light up once their keys are added to the Vercel project.
build the demo for Pivotal Health →
Nothing is generated until you ask. This reads their req and designs a document around their workflow, which costs a model call, so it happens on click.
58
medium
Crosbycrosby.ai
Extracting and verifying clauses from commercial contracts for attorney review.
posted 51d ago, still listed101-250 staff$65.8M raisedUnited States

The req that triggered this

Member of Technical Staff, Research Scientist
posted 51 days ago, still open · view posting

What they are building

The role is for an AI Researcher focusing on training models, clause extraction, and document understanding for legal tech, placing it in tier 1. No third-party extraction tools are mentioned. The experience requirement indicates a senior level.

Evidence from the posting

  • clause extraction
  • document understanding
  • human-in-the-loop workflows

Why it scored 58

+35Hiring to build extraction
+10Document pain is the business
+8Posted 5 to 9 weeks ago, still open
+5Raised in the last 12 months

Who to approach

John SarihanCTO and Co-Founderlinkedin profile

How to approach them

Crosby is hiring an AI Researcher to focus on clause extraction and document understanding for legal contracts. Since they emphasize human-in-the-loop workflows, our confidence scores and bounding boxes can directly optimize their attorney review pipeline without them needing to build verification infrastructure from scratch.

Drafted outreach

Clause extraction verification
John, I saw you are hiring an AI Researcher to work on clause extraction and document understanding for your contract review workflows. When building human-in-the-loop systems for legal documents, the bottleneck is usually verifying the model's output without reading the whole contract. We built Interfaze to solve this. It is an OpenAI-compatible endpoint that returns structured JSON along with character-level bounding boxes and confidence scores for every extracted clause. Your team can route low-confidence fields to attorneys and let them verify the text instantly on the page. If you send over a few sample contracts and a schema, we can run a diff and show you the extraction and confidence scores. Best, Michael

Act on it

Drafts only, nothing is ever sent for you. Connectors light up once their keys are added to the Vercel project.
build the demo for Crosby →
Nothing is generated until you ask. This reads their req and designs a document around their workflow, which costs a model call, so it happens on click.
58
medium
Outmarket AIoutmarket.ai
Extracting structured data from dense insurance policies for quote comparisons and policy reviews.
posted 48d ago, still listed11-50 staff$21.7M raisedUnited States

The req that triggered this

Full Stack AI Engineer
posted 48 days ago, still open · view posting

What they are building

The role focuses on building AI systems, entity extraction, and unstructured document processing using LLMs and Python, placing it in tier 1 for building extraction capabilities directly.

Evidence from the posting

  • document review, entity extraction, and quote comparison
  • unstructured documents such as PDFs or insurance policies

Other open reqs that corroborate

  • Data Engineer
  • Applied AI Scientist (PhD)

Why it scored 58

+35Hiring to build extraction
+10Document pain is the business
+8Posted 5 to 9 weeks ago, still open
+5Raised in the last 12 months

Who to approach

Anshu JainCo-founder, Chief Product & Technology Officerlinkedin profile

How to approach them

Outmarket AI is hiring an AI engineer to build entity extraction for dense insurance documents. By offering confidence scores and bounding boxes, we can help them automate human review routing for quote comparisons and policy reviews.

Drafted outreach

policy review extraction
Anshu, I saw you are hiring a Full Stack AI Engineer to build entity extraction and document review systems for unstructured PDFs and insurance policies. When extracting data for quote comparisons, a single missed limit is costly. Instead of having humans review every document, Interfaze returns a confidence score and bounding boxes for every extracted field. This lets you route reviewers only to the uncertain fields and trace values back to their exact location on the page. We are an OpenAI-compatible endpoint. You just change the base URL. If you send over a few sample policies, I can run a diff to show you the confidence scores we generate compared to your current pipeline.

Act on it

Drafts only, nothing is ever sent for you. Connectors light up once their keys are added to the Vercel project.
build the demo for Outmarket AI →
Nothing is generated until you ask. This reads their req and designs a document around their workflow, which costs a model call, so it happens on click.

Building quietly

4

Public GitHub shows these companies working on document extraction right now, but they have no scoreable job posting: no board we can read, or no matching open req. No score is invented for them. The code is the evidence, click it.

Rabbetrabbet.com
Bringing efficiency, accuracy and transparency to construction finance
DuploCloudduplocloud.com
DuploCloud provides a low-code/no-code DevOps automation platform that deploys and manages applications on AWS, GCP, and Azure by generating secure, compliant networking, database, and infra configura