#13

Chakra Labs

Commercial

medium confidence

www.chakra.dev ↗ · Status: active confirmed · Founded 2024

Chakra Labs ('Frontier Data Laboratory') builds deterministic clones of enterprise and productivity software that expose both GUI and MCP surfaces, along with verifiable task sets and crowdsourced trajectory data for training and evaluating computer-use and tool-use agents. It delivers them through its Dojo hub with Harbor, Verifiers and Verl support. In 2026 its messaging centred on task quality (difficult, realistic, reliably verifiable, hard to hack), and it published MAGI, a 1,000-task mixed GUI and MCP benchmark on which it reports frontier models below 30% pass@1.

Key facts

Headquarters

Brooklyn, New York, USAconfirmed cite

Headcount band

11-50reported cite

Total raised

$10.06Mconfirmed cite

Last round

$10.06M private placement under Reg D Rule 506(b) (Form D filed 2026-01-23; first sale 2025-12-22). Equity plus token warrants; includes $3,047,867 of convertible securities and $8,500 of token warrants. 50 accredited investors; no lead disclosed. Stage not stated in the filing.confirmed cite

SOC 2

unknown

What they sell

environmentsconfirmed cite

Open source

yesconfirmed cite

Deployment

Managed-hosted with access on request (Dojo), plus on-premises installation through Harbor per the homepage. Environments are delivered as containers, with native Harbor, Verifiers and Verl support. Internal eval and QC runs use Daytona sandboxes via Harbor.confirmed cite

What's new

3 sourced updates · last 6 months

Oct 2026hire Hiring Member of Technical Staff (New York) for agent orchestration at scale
The Simplify listing, live in early October 2026, describes 'hundreds of agent runs at once, each with its own stateful environment', '100M tokens per minute across the fleet', ownership of an SQS-based dispatch layer, and building customer-facing run-inspection dashboards, expert tooling and APIs. Simplify shows 4 open jobs for the company. Source: aggregator, so treat as reported.
Why it matters: The role points to customer-facing platform surfaces (dashboards, APIs) being built on top of the managed environment service. The scale figures are claims made in a job ad.
11 Sep 2026partnership Chakra moves QC trials from Kubernetes to Daytona sandboxes (partnership post)
In 'Quality Control as an Infrastructure Problem', David Finkelstein (Creative Director) describes migrating trials onto Daytona on-demand sandboxes via Harbor's Daytona support, a staged move that began in Q1. Comparing 58,596 Kubernetes trials (Oct 2025–May 2026) with 1,135 Daytona trials (Aug 2026), P99 sandbox start time fell from 16.7 hours to 46 seconds. Peak daily trials reached 7,544, 51% above the old peak, and cost per trial fell about 85% on a list-price basis. Daytona co-founder and CEO Ivan Burazin is quoted in the post. Chakra says each task runs at least 10 times against each frontier model during QC. The blog index dates the post 11 Sep 2026; the article header shows Sep 9, 2026.
Why it matters: The post confirms a named infrastructure partnership (Daytona), a Harbor-based execution stack and operating scale of tens of thousands of trials. It also describes the QC process (at least 10 rollouts per task per frontier model, plus verifier and judge audits). All figures are self-reported.
10 Jul 2026benchmark Chakra Labs publishes MAGI (MCP and GUI Interaction) benchmark
MAGI has 1,000 tasks (200 test / 800 train) across 8 cloned enterprise applications, all seeded with the shared state of a fictional 7-person startup, 'Terrace Labs'. Most tasks need GUI actions and MCP tool calls interleaved. They span 2–7 apps (mean 4.38) with a median of 87 steps. All models run through one adapted OpenHands harness built on Harbor. Chakra reports that frontier models complete fewer than 30% of tasks at pass@1: Opus 4.8 28%, GPT-5.5 15%, and Kimi K2.7-code lowest (its exact figure appears only in a chart). Only 21 of the 200 test tasks were solved by both Opus 4.8 and GPT-5.5. GUI-interaction errors (about 51% of failures) and early termination (about 40%) dominate. The arXiv preprint is listed as forthcoming. All results are self-reported.
Why it matters: This is Chakra's first formal benchmark and a public demonstration of mixed GUI and MCP task design with deterministic rubric-based verifiers. The 800-task train split is available on request (info@chakra-labs.com), which signals a training-data offering built on the same environments.

Founding team

Nirmal Krishnan

Co-founder and CEO (signed SEC Form D as Chief Executive Officer; Executive Officer and Director)

Bachelor's and master's at Johns Hopkins (CS/ML, computational genomics, with published papers on prostate cancer and iPSCs). Earlier work in data, markets and early-stage startups (per his chakra.dev author bio).

Profile ↗

Alexander Fung

Co-founder; Director

University of Waterloo (per LinkedIn). Prior roles at Palantir, Snap and Fin are reported in search snippets only and not confirmed on a primary page.

Profile ↗

What practitioners should know

For researchers

MAGI (2026-07-10) has 1,000 mixed GUI and MCP tasks across 8 cloned enterprise apps, all sharing one seeded company state. Self-reported pass@1 is Opus 4.8 28% and GPT-5.5 15%, with Kimi K2.7-code lowest. Runs use one adapted OpenHands harness on Harbor rather than native harnesses, and the arXiv preprint has not been posted.
MAGI's failure analysis finds GUI-interaction errors (about 51% of failed trajectories) and premature termination (about 40%) dominate, while MCP tool errors are near zero. Reward drops sharply on tasks spanning 6 or more apps.
Public data on Hugging Face: dojo-bench-mini (219 tasks, no license) and pango-sample (crowdsourced trajectories). The full Pango dataset and other sets are gated.
The GitHub org contains original repos (GLADOS-1, a computer-use model post-trained on crowd-sourced trajectories, Apache-2.0; and dojo-spas) plus forks. 'marina' and 'harbor' are forks of harbor-framework/harbor, and software-agent-sdk, Office-Word-MCP-Server and cli-mcp-server are forks of third-party projects.
Editorial stance (Nirmal Krishnan, Jan 2026): 'Labs are not buying environments, they are buying tasks.' Good tasks are difficult, realistic, reliably verifiable and hard to hack, and Chakra cites pass@5 below 30% as the difficulty range labs expect.

For program managers

Published onboarding model (methodology page, undated): Discovery 3–5 days, Provision 2–3 days, Benchmark 1–2 days, Train (highly variable), New Benchmark 1–2 days. That is about 7–12 days plus training time. The page also claims custom task specification to evaluation-ready deployment in under 24 hours (self-claimed).
No named customers. The site cites unnamed 'leading research teams', which is self-claimed. The Hugging Face org has gated datasets with codename labels (e.g. pango-customer-*, dojo-bench-customer-colossus), but no customer identities are disclosed.
Funding: one SEC Form D (filed 2026-01-23, first sale 2025-12-22) shows $10,056,320 sold to 50 accredited investors. The total includes $3,047,867 of convertible securities and $8,500 of token warrants. No lead investor or valuation is disclosed, and no new round was found in Apr–Oct 2026.
Named infrastructure partner: Daytona (sandboxes). Its CEO is quoted in Chakra's Sep 2026 post.
Team: Simplify reports 11–50 employees and 4 open roles, including an in-person MTS role in New York (aggregator data, reported).

For data ops

Integration: Dojo supports Harbor, Verifiers and Verl natively. Environments ship as containers, hosted or on-prem via Harbor (per the homepage). MAGI runs through an OpenHands harness on Harbor.
Execution backend: Daytona on-demand sandboxes via Harbor. Self-reported P99 start time fell from 16.7 hours to 46 seconds, and cost per trial fell about 85% at list price.
QC process (self-described): each task is run at least 10 times per frontier model. RLVR verifiers are audited against a judge for false positives and negatives, LLM-judge tasks are checked for agreement with human reviewers, and expert operators produce golden traces before a task ships.
No SOC 2 or other certification and no security page found. Contacts are info@, partner@ and pr@chakra-labs.com.

Benchmarks & research

4 published

MAGI: MCP and GUI Interaction benchmarkbenchmark · 10 Jul 2026

1,000 tasks (200 test / 800 train) across 8 cloned enterprise applications seeded with a shared fictional company state. Tasks need GUI interaction and MCP tool use interleaved and span 2–7 apps. Each task carries about 12–20 deterministic sub-checks, scored as pass@1 plus mean reward. Models are evaluated through a single adapted OpenHands harness on Harbor, not native harnesses. The arXiv preprint is listed as forthcoming. Self-published by Chakra Labs.

Self-reported: frontier models complete fewer than 30% of tasks at pass@1. Opus 4.8 scores 28%, GPT-5.5 15%, and Kimi K2.7-code is lowest (exact value shown only in a chart). Only 21/200 test tasks are solved by both Opus 4.8 and GPT-5.5.

Open ↗

Dojo-SPAsenvironment · 19 Feb 2026

Mocked single-page applications for evals and RL (original Chakra repo, no declared license). The date is the last push.

Open ↗

Dojo-Bench-Minidataset · 13 Oct 2025

Small public task set for computer-use agents against mocked productivity apps and games: 219 rows, no declared license. The files cover Amazon, Gmail, Linear, LinkedIn, Microsoft Teams, Outlook, Salesforce, Slack, Tic-Tac-Toe, 2048 and Minesweeper, each with Python reward functions.

Self-reported chart on the chakra.dev homepage: Claude Opus 4.6 41.39%, 'ChatGPT 5.2-High' 29.51%, Gemini 2.5 Pro 9.43%, Llama 4 Maverick 3.69%.

Open ↗

Pango Sample (crowdsourced computer-use trajectories)dataset · 21 Jul 2025

Public sample of 'Pango' (Productivity Applications with Natural GUI Observations): real computer-interaction data from paid crowd contributors doing real work in productivity apps. The full Pango dataset is gated (manual approval).

Open ↗

Products

Dojo ↗

Collaborative RL environment hub for computer-use research: interactive clones of production software with native support for Harbor, Verifiers and Verl. Access is by request only.launched 5 Oct 2025

Chakra environment clones ↗

Deterministic, pixel-perfect environment clones exposing GUI and MCP surfaces. The site lists Notion, Figma, Canva, Gmail, LinkedIn, Salesforce, Amazon, Slack, GitHub, Grafana and Google Calendar. Delivered by containerization, either hosted or on-premises through Harbor (per the homepage).

MAGI benchmark and train split ↗

1,000-task benchmark mixing MCP and GUI. Teams can ask to run their model on it, and the 800-task train split is available on request.launched 10 Jul 2026

Pango trajectory datasets ↗

Crowdsourced human computer-use trajectories from productivity applications. A public sample is available; the full dataset is gated.

Scale & velocity

Current headcount

~14reported cite

Headcount growth

unknown

Open roles

4 (Simplify listing; includes Member of Technical Staff, New York)reported cite

Other locations

unknown

Distributed / remote

unknown

Research depth

Has researchers

yesreported cite

Researcher count

unknown

Backgrounds

Nirmal Krishnan (co-founder and CEO per the SEC Form D signature): Johns Hopkins BS/MS (CS/ML, computational genomics); prior data, markets and early-stage startups, Alexander Fung (co-founder; Director per SEC Form D): University of Waterloo; reported ex-Palantir, Snap and Fin (snippets only), David Finkelstein (Creative Director, not a researcher): leads creative and editorial strategyreported cite

Capital

Total raised

$10.06M (SEC Form D, Chakra Digital Labs, Inc., filed 2026-01-23; includes about $3.05M of convertible securities)confirmed cite

Last round

Investors

unknown

Valuation

unknown

Revenue signals

unknown

Security & compliance

SOC 2

unknown

Other certifications

unknown

Security page

unknown

Product

What they sell

environmentsconfirmed cite

Open source

yesconfirmed cite

License

Mixed. Original Chakra repos: GLADOS-1 is Apache-2.0; dojo-spas and verl-tools have no declared license. Forks: marina and harbor (of harbor-framework/harbor, Apache-2.0), software-agent-sdk (of OpenHands, MIT), Office-Word-MCP-Server and cli-mcp-server (third-party, MIT). The dojo-bench-mini HF dataset declares no license.confirmed cite

Deployment model

Maturity

private beta (request access)estimated cite

Notable customers

unknown

Buyer analysis

Best fit: Teams training or evaluating computer-use and tool-use (MCP) agents on long-horizon, multi-application enterprise workflows that need deterministic software clones, rubric-verified tasks and a Harbor-compatible harness.

How we verified this

2026-10-05 refresh: I opened every cited primary page and pulled raw HTML where the summarizer was unreliable. That surfaced two significant errors in the draft. First, the MAGI leaderboard included a fabricated 'Fable 5 25%': Fable 5 was not evaluated, and the 85.0% on the page is its OSWorld-Verified score. Second, the '2026-10-02' dates on MAGI and the methodology page are a site-wide Framer build timestamp. MAGI is dated 2026-07-10 per the blog index, and the methodology page is undated, so it was dropped as news. The Kimi pass@1 number is not in the page text and was removed. The GitHub API showed Marina and the MIT MCP repos are forks, so the Marina news item was dropped and the license framing corrected. The SEC Form D XML confirmed $10,056,320 sold to 50 accredited investors, including $3,047,867 of convertibles and $8,500 of token warrants, plus incorporation in 2024. It also shows Nirmal Krishnan signing as CEO, which I added. The funding event itself predates the window, so it moved from funding_events to field updates. EDGAR shows no later filing, and I found no new round. The Daytona QC post figures and the Simplify MTS quotes were verified verbatim. LinkedIn profile titles confirm both founders at Chakra Labs. Krishnan's photo comes from his chakra.dev author byline and was verified as a single-person headshot that appears only next to his name; no verifiable photo exists for Fung. I added the Pango trajectory datasets from the HF org. Limitation: the web-search budget was exhausted, so the sweep for missed third-party coverage (press, acquisitions, frontier-lab partnerships) covered only primary sources (chakra.dev blog index, EDGAR, GitHub, HF), and none of those showed a new round or status change.

Related vendors

Sources

www.chakra.dev/ · 2026-10-05, Homepage: environment clones (GUI and MCP), hosted and on-prem via Harbor, dojo-bench-mini chart, unnamed 'leading research teams'
www.chakra.dev/blog · 2026-10-05, Blog index with dates: Dojo 5 Oct 2025; editorials 7 Jan, 9 Feb, 8 Mar 2026; MAGI 10 Jul 2026; QC post 11 Sep 2026
www.chakra.dev/research · 2026-10-05, Publications index (same dates as the blog index)
www.chakra.dev/magi-bench · 2026-10-05, MAGI page: tasks, harness, Opus 4.8 28% and GPT-5.5 15% pass@1, failure taxonomy, BibTeX. The 2026-10-02 value in the HTML is a Framer build timestamp, not a publication date
www.chakra.dev/blog/quality-control-as-an-infrastructure-problem · 2026-10-05, Daytona/Harbor migration post by David Finkelstein, with latency, scale and cost figures and a Daytona CEO quote
www.chakra.dev/methodology · 2026-10-05, Undated five-phase onboarding model and claims about bespoke task generation
www.chakra.dev/blog/rl-environments-are-worthless · 2026-10-05, Jan 2026 editorial by Nirmal Krishnan; author bio and byline headshot
trydojo.ai/ · 2026-10-05, Dojo: request access; Harbor, Verifiers and Verl support
huggingface.co/datasets/chakra-labs/dojo-bench-mini · 2026-10-05, Public dataset; 219 rows confirmed via datasets-server; created 2025-10-13; no license
huggingface.co/datasets/chakra-labs/pango-sample · 2026-10-05, Public Pango sample of crowdsourced computer-use trajectories (via HF API)
github.com/chakra-network · 2026-10-05, Repos, licenses and fork status via the GitHub API; marina is a fork of harbor-framework/harbor (last push 2026-08-27)
www.sec.gov/Archives/edgar/data/2106724/000123191926000079/primary_doc.x · 2026-10-05, Form D for Chakra Digital Labs, Inc.: $10,056,320 sold, 50 investors, $3,047,867 convertibles, incorporated 2024, signed by Nirmal Krishnan as CEO
www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0002106724&type=D · 2026-10-05, EDGAR issuer page: Brooklyn address, Delaware; the only filing is the 2026-01-23 Form D
alleywatch.com/2026/02/nyctech-week-in-review-1-25-26-1-31-26/ · 2026-10-05, Reports $10.1M from fifty investors; founders Fung and Krishnan, 2024
simplify.jobs/c/Chakra-Labs · 2026-10-05, Aggregator: 4 open jobs, 11–50 employees (reported)
simplify.jobs/p/6a8b3f39-c088-40a1-874e-d0a0f909b9ef/Member-of-Technical · 2026-10-05, MTS role in New York; orchestration scale description
www.linkedin.com/in/nirmal-krishnan · 2026-10-05, Public profile title: Chakra Labs; Johns Hopkins; New York
www.linkedin.com/in/alexfung · 2026-10-05, Public profile title: Chakra Labs; University of Waterloo; New York
arxiv.org/abs/2609.04298 · 2026-10-05, Harbor-Index paper checked; Chakra Labs is not mentioned or credited
www.chakra.dev/publications/product-launch-dojo · 2026-06-07, Dojo launch (2025-10-31); product description; Nirmal Krishnan co-founder note; no named customers
www.linkedin.com/company/chakra-labs · 2026-06-07, Public snippet, Data Infrastructure & Analytics; '2-10' size band with 14 total employees noted; founders Fung & Krishnan listed
www.alleywatch.com/2026/01/the-alleywatch-startup-daily-funding-report-1 · 2026-06-07, Reports Chakra Labs $10.1M funding per SEC filing (2026-01-26), ~50 investors; founded 2024 by Alexander Fung & Nirmal Krishnan
x.com/chakra_ai · 2026-06-07, Company X account; Computer Use Agents Part I & II market-map posts
www.crunchbase.com/organization/chakra-labs · 2026-06-07, Listing (HTTP 403 on fetch); referenced via search snippets for Brooklyn/NY HQ and founder data
jobs.ashbyhq.com/chakra-labs · 2026-06-07, Careers page; listings not extractable from public snippet

Last updated 2026-10-05 · Every quantitative field carries a source and a confidence tag. Fields we could not source publicly are marked unknown, never estimated. See the methodology.