DevHawk
DevHawk is an AI software factory: seven specialist agents, directed by senior engineers, that build, ship and run business software. Companies either let DevHawk operate the factory or buy the agents and run them in-house.
What is DevHawk?
DevHawk bills itself as the AI software factory, under a home page line that reads software, built like it's 2026. It is not a product you sign up for. It is an engineering service sold on a monthly engagement, and the only way in is a booked call. The company behind it is GXHR Inc., which traded as Fraction from 2022 before rebranding to DevHawk in 2026.
The factory is a starting lineup of seven specialist agents - DevOps, Engineering, Code Review, Security, QA Automation, Site Reliability and Project Management - which, in DevHawk's words, work in parallel so nothing waits in a queue. Between them they span nine billable capabilities: product ownership, software architecture, AI engineering covering LLMs, RAG and agents, automated QA, infrastructure and monitoring, secure deployment, data architecture, mobile and cross-platform UX, and AI enablement. Most engagements use three to five of them, and the rest are never billed.
Two delivery models sit on the same stack. We Run It starts at 9,000 dollars a month with a three-month minimum: DevHawk holds the AI keys, model usage is included, and it carries delivery, oversight and incidents. You Run It starts at 3,000 dollars a month plus a one-time 9,000 dollar onboarding month, after which your own team runs the agents with your own API keys, pays model usage directly and gets Slack support. You can start with a single agent or with all seven.
Humans keep the wheel. Senior engineers direct the agents, a senior engineer reviews and directs every commit before it merges, and on the managed plan DevHawk promises senior US-based engineers with no juniors and no offshore. As the site puts it: the agents do the parallel execution; humans make every call that matters.
DevHawk advertises delivery up to 10x faster at 80% less cost than the old way, and 175+ companies served under the Fraction name - its own claims, not audited figures. It shows work in wealth management and fintech, healthcare, logistics and transportation, and construction and real estate. A separate offer, the AI Audit, is a flat 8,000 dollar, two-week engagement run personally by founder Praveen Ghanta, with six written deliverables and a vendor-neutral result. Whatever the model, the client owns the code, repositories, infrastructure, credentials and documentation from day one.
What it does
- Turn every user story into production-ready code across your chosen stack.
- Review each pull request before a human sees it, flagging logic errors, security anti-patterns, test coverage gaps and regressions with context and suggested fixes.
- Build and maintain CI/CD pipelines, environment configuration and deployment automation.
- Scan continuously for vulnerabilities during sprints: exposed secrets, injection risks, unsafe dependencies and OWASP Top 10 violations.
- Write and run test suites alongside the features themselves, with incremental regression coverage.
- Watch production around the clock for uptime, latency and error rates, and raise an alert at the first sign of degradation.
- Track sprint velocity, surface blockers before they spread, and produce progress reports for stakeholders.
When to use DevHawk / When not to
A quick filter to help you decide if DevHawk is the right fit.
When to use DevHawk
- Founders and executives whose company has no in-house engineering team and who want a full delivery operation without hiring, onboarding or managing anyone.
- Engineering leaders of 5 to 50-person teams that adopted AI tools but have not seen the productivity gains they expected.
- SaaS and fintech operators heading into private-equity diligence, a re-architecture or a scaling inflection point, who need an outside read on their systems.
- Product organizations chasing a faster release cadence with developers already in place, in-house or offshore, whose output the agents are meant to lift.
- Companies in wealth management, fintech, healthcare, logistics, construction, proptech or legal services with 3,000 to 9,000 dollars a month to spend, including those planning to build their own engineering team later.
When not to use DevHawk
- Companies with less than 3,000 dollars a month to commit, or unable to absorb the one-off 9,000 dollar onboarding fee that comes with the self-run plan.
- One-off needs shorter than three months: the managed plan carries a three-month minimum, which DevHawk defends by saying a shorter engagement would sell you the most expensive month and none of the payoff.
- Individual developers and small teams shopping for a self-serve coding assistant: there is no sign-up, no account, no free plan and no trial.
- Buyers who want to evaluate a product before talking to anyone: the only way in is booking a systems review through the site's calendar.
- Organizations whose procurement requires published compliance commitments (GDPR terms, a DPA, a subprocessor list, a hosting jurisdiction) or public technical material such as an API, a mobile app or documentation: DevHawk publishes none of it, and the site has no terms of service page at all.
How to use DevHawk
A typical end-to-end flow, from setup to results.
- Book a systems review on the DevHawk site through its embedded calendar; the company describes it as a working conversation, not a sales call.
- Walk through your systems, your team and where you are stuck. No pitch deck is expected, and DevHawk says you leave with clarity whether you work together or not.
- Optionally start with the AI Audit, a flat 8,000 dollars over two weeks, and walk away with a written playbook before committing to anything.
- Choose your delivery model: We Run It, where DevHawk operates the factory, or You Run It, where your own team does.
- Scope the capabilities you actually need out of the nine on offer - most engagements need three to five - and pay only for those.
- On We Run It, DevHawk holds the AI keys with usage included, the engagement runs for a three-month minimum, and delivery, oversight and incident response sit on DevHawk's side.
- On You Run It, bring your own AI API keys and pay model usage directly; the first month is hands-on integration into your workflows plus training for your engineers, billed once at 9,000 dollars.
- Start with one agent or with all seven, depending on how much you want to change at once.
- After onboarding, run day-to-day support through Slack, which is included in the subscription.
- Adjust the mix of capabilities as your systems change and, when the time comes, take the work in-house: DevHawk says everything is documented for that day from day one and that it helps with the switch.
Pros & Cons
Pros
- Entry prices are published in plain sight - 3,000 dollars a month self-run, 9,000 dollars a month managed, 8,000 dollars for the audit - which is rare for an engineering services firm.
- Clients own the code, repositories, infrastructure, credentials and documentation from day one, not at contract end.
- A senior engineer reviews and directs every commit before it merges, so the AI never merges on its own.
- Billing is limited to the capabilities actually used, and the mix can be adjusted as your systems change.
- The exit is planned rather than avoided: DevHawk says everything is documented from day one for the day you move to your own hires, and that it helps with the transition.
- Sector depth is documented: DevHawk claims 175+ companies served under the Fraction name, citing work for SEC-registered advisory firms, EHR integrations and construction ERPs.
- The AI Audit leaves you with a reusable deliverable and, in DevHawk's words, you are never obligated to hire them afterwards.
Cons
- Nothing is self-serve: no sign-up, no account, no demo. Every path starts with a call you have to book.
- The entry ticket is high: 3,000 dollars a month plus a one-time 9,000 dollar onboarding, or 9,000 dollars a month with a three-month minimum.
- There is no free plan and no free trial of the service itself.
- No terms of service page is published, so liability, intellectual property and confidentiality cannot be read before you enter a relationship.
- The privacy policy is silent on the GDPR, DPAs, subprocessors, hosting jurisdiction and retention, while the verticals on display involve regulated health and financial data.
- That policy still describes an SMS talent-matching program inherited from the Fraction era, and the published support address remains on the legacy fraction.work domain: the document has not been rewritten for the current business.
- No API, no mobile app and no public technical documentation: there is nothing to assess technically before the sales conversation.
Pricing & Plans
There is no free plan and no free trial of the service. The lowest paid entry point is the You Run It self-run model, from USD 3,000 per month, to which DevHawk adds a one-time onboarding fee of USD 9,000 in the first month. The managed We Run It model starts at USD 9,000 per month with a three-month minimum, billed on an ongoing basis. The standalone AI Audit is a flat USD 8,000 for a two-week engagement, presented as a flat fee with no surprises. Only the 30-minute introductory call and the systems review are free of charge. AI model usage is included on the managed plan, where DevHawk holds the keys, and is billed directly to the client by its own AI provider on the self-run plan. DevHawk states that the fee follows the deployment model rather than a menu of hours, and that only the capabilities retained are billed. All amounts are quoted in US dollars; no annual pricing, commitment discount or public tier beyond these floors is advertised.
- from USD 9
- 000 per month
- three-month minimum
- ongoing. DevHawk operates the factory for you and carries delivery
- oversight and incident response. AI usage is included and DevHawk holds the keys
- you own the code and infrastructure from day one.
- from USD 3
- 000 per month plus a one-time USD 9
- 000 onboarding in the first month. You pick your capabilities and run the agents with your own team
- with training
- integration and setup done alongside you and Slack support included in the subscription
- the AI keys and the model bill are yours.
- USD 8
- 000 flat for two weeks from kickoff to playbook
- run personally by Praveen Ghanta
- in two variants (Business & Operations Audit or AI Readiness Audit)
- with a vendor-neutral deliverable and a free 30-minute introductory call.
Data, GDPR & hosting
A consolidated view of how DevHawk handles your data.
GDPR overview
There is no mention of the GDPR anywhere on devhawk.ai: the term does not appear once, privacy policy included. No DPA, no subprocessor list, no Article 27 representative, no transfer mechanism and no retention period are published. The policy is built for United States law, with a TCPA-style SMS program, support for all major U.S. carriers, and a CCPA-style right to opt out of the sale or sharing of personal information. Rights are conditional - depending on your jurisdiction and applicable law, the text says, you may have certain rights - and cover access, correction, deletion, SMS unsubscribe and that opt-out. DevHawk promises an answer within the timeframe required by applicable law, typically 30 to 45 days, may verify your identity first, and will not discriminate against anyone exercising these rights. Requests go to privacy@devhawk.ai or info@fraction.work. European buyers should expect to negotiate every GDPR term privately.
Who owns the data?
With no terms of service published, ownership can only be read from the privacy policy and the home page. On the delivery side, the site states twice that the client owns everything built - code, repositories, infrastructure, credentials, documentation - from day one, not at contract end. On the website side, GXHR Inc., operating as DevHawk, controls the personal data it collects: contact, transaction, geolocation, browsing history, professional and protected-classification data. It says it shares nothing with outside third parties, uses aggregated non-identifying data to improve its services, requires its contracted providers to apply safeguards without naming any of them, and holds you liable for third-party data you submit.
Reuse rights
Clients can reuse what DevHawk builds without asking: the site states that code, repositories, infrastructure, credentials and documentation belong to the client from day one, and that a handover to an internal team is documented from the start. The AI Audit playbook is explicitly free of strings, with the site saying the plan is yours and you may use it with anyone, including another vendor or nobody at all, with no obligation to hire DevHawk afterwards. Everything beyond that is unverifiable in advance: with no terms of service published, licensing, intellectual property and confidentiality clauses cannot be read before you make contact. The site also never says whether models are trained on client code or data, in either direction. For the website itself, the privacy policy notes that information may be stored locally on your device, for instance in your cache, and that aggregated non-identifying information may be used to operate and improve the services.
Data retention & training
Hosting summary
DevHawk publishes no hosting jurisdiction. No country, region, data center or cloud provider is named anywhere on the site, and no certification is claimed, neither SOC 2 nor ISO 27001; HIPAA-ready appears as a sector skill, never as a certification. The privacy policy describes safeguards rather than locations: encryption in transit over standard protocols, role-based access controls with strong authentication, data minimization, contractual security obligations on third-party providers, and monitoring for unauthorized access. It also states that DevHawk does not share information with outside third parties, and carries the standard caveat that no method of internet transmission or electronic storage is completely secure. The only published geographic anchor is the GXHR Inc. headquarters in Atlanta, Georgia. Two distinctions matter. For client engagements, the infrastructure belongs to the client from day one, so the systems DevHawk builds live wherever the client hosts them. And the marketing site itself is served behind Cloudflare, which concerns website delivery only and says nothing about where client data would sit.
Things to keep in mind
Risks and trade-offs to weigh before adopting DevHawk.
- The performance figures are the vendor's own and unaudited: up to 10x faster, 80% less expensive, 99.99% uptime and a 142 tests green status banner, none of which can be verified from outside.
- Nothing is published on the GDPR, DPAs, subprocessors, hosting jurisdiction or retention, while the verticals on display involve health records and SEC-registered firms.
- With no terms of service at all, liability, intellectual property, confidentiality and termination conditions cannot be read before you enter a relationship.
- Concentration risk: handing both the building and the running of your systems to a single supplier puts a lot of your operation in one place, even with a documented handover promised.
- Skill erosion: delegating ongoing, repeatable work to agents can starve your junior developers of the very tasks they learn on.
- Financial exposure cuts both ways: the managed plan asks for a three-month commitment before you have seen a result, the first month being explicitly spent learning your systems, while the self-run plan has you bring your own AI keys and pay model usage directly with no cap announced.
- High-volume AI-generated code: automated review and vulnerability scanning lower the risk but do not remove the need for an independent human security review.
Setup & Integrations
Technical difficulty
There is no self-serve setup: entry is by booking a systems review on the site's calendar. On the managed plan, client effort is close to zero, with nobody to recruit, onboard or manage and DevHawk holding the AI keys. The self-run plan asks more of you: a first month of hands-on integration into your workflows and training for your engineers, billed once at 9,000 dollars, plus your own AI API keys, an existing dev team and existing repositories. You can start with one agent or all seven. No public technical documentation exists to prepare in advance.
Integrations
Behind DevHawk
Resources
All the official URLs gathered for verification and reference.
Frequently asked questions
Why is there a three-month minimum?
What happens if we build an in-house team later?
What sets the monthly price?
Who actually does the work?
What does the client own?
How much does it cost?
What is the AI Audit?
Which agents make up the offer?
Is there a free plan or a free trial?
Does DevHawk publish GDPR commitments or a DPA?
Should you pick DevHawk?
DevHawk is not a tool you try out. It is an AI-agent engineering service sold on a monthly engagement, and every road in leads through a booked call. What sets it apart is the pair of delivery models sitting on one agent stack - DevHawk operates the factory, or your own team does - together with published price floors, immediate client ownership of everything built, and a senior engineer reviewing and directing every commit before it merges.
The reassurance is tangible: 175+ companies served under the Fraction name since 2022, a team named on the record, and two signed, quantified case studies from Bruce Orr, CEO of ProNovos, and Bhavik Paryani, founder of Paryani Construction. The exit is planned rather than papered over, with documentation prepared from day one for clients who later hire their own engineers.
The gaps are just as concrete. There is no terms of service page anywhere on the site, and no mention of the GDPR, a DPA, subprocessors, hosting jurisdiction or retention periods - an uncomfortable silence given the healthcare and finance work on display. There is no API, no application, nothing you can assess technically without a sales conversation. And the headline numbers, up to 10x faster, 80% less expensive, 99.99% uptime, are DevHawk's own claims rather than audited measurements.
Budget honestly: 3,000 dollars a month plus 9,000 dollars of onboarding on the self-run plan, or 9,000 dollars a month over at least three months on the managed one. For a prospect who wants to test the thinking before the commitment, the lowest-risk door is the 8,000 dollar AI Audit, whose playbook DevHawk says you may use with anyone. Ask for the contract terms in writing before you sign.
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