RLTX StrikeOps
Mission Ops for Frontier Labs
When your models and agents need serious evals, safety campaigns, or high-signal data fast, we design the mission, assemble elite researchers, orchestrate vendors, and deliver.
When you’re out of bandwidth for evals, safety work, or high-signal data, we deploy elite research pods to run the experiments you can’t—delivering launch-critical missions in weeks not months.
Backed by operators and researchers from
What is RLTX StrikeOps?
Your External Research Missions Layer
You already have GPUs and general‑purpose data vendors. StrikeOps is the layer for high‑stakes research work around your models and agents.
We design high‑stakes research missions
Launch readiness, agent evals, safety campaigns, and data/env prototypes—each mission has a clear question, methodology, and deliverables.
We plug into your stack and assemble the pod
We work inside your eval harnesses, sandboxes, and workflow tools, then assemble the right mix of RLTX researchers + your team + existing vendors.
We own execution, QA, and evidence
A mission lead you’d hire yourself runs the pod end‑to‑end and hands back code, results, and concise technical memos your leaders can actually make decisions from.
Research, Not Scale
Why Now: The Age of Research
For a decade, the game was simple: scale models, buy more compute, collect more generic data.
That curve is flattening. The bottleneck now is research:
Finding the right evals and benchmarks
Understanding agent behaviour under tools and pressure,
running serious safety campaigns,
prototyping new data and environments before you commit billions.
We aren’t short of ideas—but short of bandwidth to run clean experiments.
RLTX exists to be that bandwidth: a small, brutally high‑quality research missions layer that plugs directly into your stack.
RLTX exists to be that bandwidth: a small, brutally high‑quality research missions layer that plugs directly into your stack.
MISSIONS WE RUN
Productized research missions,
not vague consulting.
01
Launch Mission – Frontier Model / Agent
Launch Mission –Frontier Model / Agent
Ship a new model or agent with real experiments.
Eval & safety design tied to your risk profile and use cases
Human + AI feedback loops (RLHF/RLAIF where it actually matters)
Datasets, metrics, and decision docs wired to your launch gates
02
Safety & Red-Team
Stand-Up
Stand-Up
Go from “we should red‑team this” to a standing safety research program.
Frontier-aligned threat models tailored to your policies.
Experts and red-teamers fluent in tools, agents, and workflows.
Ongoing findings and coverage you can feed into training and launch.
03
Expert Network Blitz
When you need a fast, credible research network around a tough surface.
Align on what “expert” means across agents, infra, safety, and domain.
Source, test, and calibrate researchers through our networks.
Provide a vetted cohort ready for evals, safety studies, and experiments.
04
Custom Missions –
Bring Us Your Weird
Bring Us Your Weird
For problems that don’t fit a template but are too important to ignore.
Evals spanning domains, jurisdictions, markets, and languages.
Real-time “shadow production” research catching and testing edge failures.
Repeatable gauntlets for sensitive domains—misuse, safety, compliance.
Triage missions for when it’s on fire—hot-fix evals, red-teaming, and evidence in days.
HOW IT WORKS
From “We Have a Deadline” to “Mission Complete”
Mission Brief
You send us a short brief: what you’re shipping, where you’re worried, what infra you already have. In a 60–90 minute session we turn that into a concrete research mission with questions, methods, constraints, and success criteria.
Pod Assembly
We pick a mission lead and elite researchers from our network, plus any external vendors / internal teams we need to interop with (Mercor, existing labelers, environment providers, your ops).
Execution & Check‑ins
Over 2–4 weeks we run the experiments, evals, or campaigns. You get lightweight weekly updates and early samples so there are no surprises.
Delivery & Hand-Off
You get datasets, evals, and reports plus playbooks and configs for future runs.Many partners convert successful missions into ongoing programs.
WHO WE WORK WITH
Teams Where Failure Isn’t an Option
Frontier and foundation model labs
Defense and national security programs using AI systems
Financial, healthcare, and critical-infra organizations deploying high-stakes AI
We work with a small number of frontier labs and high‑stakes programs at a time so we can stay close to the work. When we say yes to a mission, it matters to us.
Research Missions in the Wild
Mission Types That Support
Frontier Development
Frontier Lab – Launching a Frontier Agent
A frontier lab is 8 weeks away from shipping a new agent system that writes and ships code. Internal eval and safety teams are overloaded. They have Mercor and internal contractors, but no one owning the whole mission.
Learn More
Defense Ministry – Neutral Evaluation of Three Labs
A Ministry of Defense wants to choose between models from Lab A, Lab B, and Lab C for a sensitive intel/ops program. Each lab has their own evals and vendors (including Mercor‑type partners), but the ministry needs a neutral, apples‑to‑apples test range and report.
Learn More
Tier‑1 Bank – Joint Program with a Frontier Lab Under Regulator Scrutiny
A global bank wants to deploy a frontier model from Lab X for customer‑facing and risk workflows. Their regulator is already nervous. The bank has data teams, the lab has their own eval suite and Mercor‑style vendors, but no one is responsible for the joint, regulator‑grade program.
Learn More
Frontier Lab – Launching a Frontier Agent
A frontier lab is 8 weeks away from shipping a new agent system that writes and ships code. Internal eval and safety teams are overloaded. They have Mercor and internal contractors, but no one owning the whole mission.
Learn More
Defense Ministry – Neutral Evaluation of Three Labs
A Ministry of Defense wants to choose between models from Lab A, Lab B, and Lab C for a sensitive intel/ops program. Each lab has their own evals and vendors (including Mercor‑type partners), but the ministry needs a neutral, apples‑to‑apples test range and report.
Learn More
Tier‑1 Bank – Joint Program with a Frontier Lab Under Regulator Scrutiny
A global bank wants to deploy a frontier model from Lab X for customer‑facing and risk workflows. Their regulator is already nervous. The bank has data teams, the lab has their own eval suite and Mercor‑style vendors, but no one is responsible for the joint, regulator‑grade program.
Learn More
Frontier Lab – Launching a Frontier Agent
A frontier lab is 8 weeks away from shipping a new agent system that writes and ships code. Internal eval and safety teams are overloaded. They have Mercor and internal contractors, but no one owning the whole mission.
How it plays out (workflow):
1. They call RLTX.
- Head of Safety / Agents sends: “We need to know if this thing is safe and reliable enough to ship, and we don’t have time to glue all the pieces together.”
2. We design the mission, not just tasks.
- StrikeOps sits with their researchers and safety team for a Mission Brief: define objectives, risk surfaces (jailbreaks, data exfiltration, code‑level failures), timelines, and success criteria.
3. We pick and wire the components.
- Use their preferred environment stack (e.g., Mechanize‑style work ranges, internal sandboxes).
- Pull in human supply from Mercor/Turing + our expert network + their own annotators.
- Define roles: red‑teamers, domain experts, PH pods, QA leads.
4. We run the mission end‑to‑end.
- Orchestrate tasks across all vendors and internal people.
- Operate RL‑style environments and work test ranges.
- Calibrate and QA humans across time zones; handle all the boring ops.
5. We hand them a launch packet.
- Capability and safety metrics in the language their CTO/board understands.
- Coverage maps vs their internal policies and frontier safety frameworks.
- Concrete recommendations: “Ship with these guardrails, here’s what to monitor.”
Learn More
Defense Ministry – Neutral Evaluation of Three Labs
A Ministry of Defense wants to choose between models from Lab A, Lab B, and Lab C for a sensitive intel/ops program. Each lab has their own evals and vendors (including Mercor‑type partners), but the ministry needs a neutral, apples‑to‑apples test range and report.
How it plays out (worflow):
1. The buyer (MoD) calls RLTX.
- Their program office says: “We need an independent mission to evaluate these three labs on capability and safety, and we need to be able to defend the choice to parliament.”
2. We design a neutral test range and standard.
- RLTX defines the mission: scenarios, RL‑style environments, threat models, performance & safety metrics.
- Agree the rules with the ministry and all three labs.
3. We orchestrate across labs and vendors.
- Use each lab’s models behind their firewalls.
- Plug in environment vendors (Mechanize/Habitat/internal sims) as needed.
- Pull human operators from Mercor/Turing, defense SMEs, and our own expert network.
- Everyone works to a single RLTX playbook.
4. We run the eval & red‑team campaign.
- Same tasks, same environments, same standards across all models.
- Continuous QA and calibration, regardless of which vendor supplied the humans.
5. We deliver one integrated report.
- Side‑by‑side comparison of the three labs: capability, robustness, safety, failure modes.
- Clear recommendation with traceable evidence.
- Documentation that can be handed to oversight bodies, auditors, and internal command.
Learn More
Tier‑1 Bank – Joint Program with a Frontier Lab Under Regulator Scrutiny
A global bank wants to deploy a frontier model from Lab X for customer‑facing and risk workflows. Their regulator is already nervous. The bank has data teams, the lab has their own eval suite and Mercor‑style vendors, but no one is responsible for the joint, regulator‑grade program.
How it plays out:
1. The bank (or Lab X) calls RLTX.
- “We need a joint mission across us + the lab that ends with something we can take to the regulator and our internal risk committee.”
2. We design a three‑party mission.
- RLTX StrikeOps pulls in stakeholders from:
- the lab (model/eval/safety),
- the bank (risk, compliance, business),
- and, indirectly, the regulator’s expectations.
- Define use cases, failure modes, jurisdictions, and what “acceptable risk” looks like.
3. We assemble the human + environment stack.
- Use the lab’s models and internal tools.
- Stand up RL‑style environments and work test ranges around the bank’s real workflows (loans, KYC, trading support, etc.).
- Orchestrate data labeling / eval workers from Mercor/Turing, PH pods, and specialized finance SMEs.
4. We run the campaign and iterate.
- Stress‑test the model/agents against real bank processes and adversarial scenarios.
- Capture failures, mitigations, necessary control changes.
- Work with the lab to patch and re‑test.
5. We produce a regulator‑ready pack.
- Evidence that the bank can show to supervisors: methods, metrics, risks, controls.
- Internal docs for the bank’s model risk committee and the lab’s leadership.
Learn More
FAQs
Everything you need to know about us
Are you just reselling Mercor or other labor networks?
How fast can you stand up a serious program?
How do you guarantee quality?
How do you work with our internal teams and existing vendors?
What does pricing look like?