Every major model in one workspace, keeping your context and progress intact.
Switch between Claude, GPT, Gemini, and more inside any chat. Your context, files, and project carry over, so if one model goes dark, you switch and keep working. No lock-in.
Free to start. Your context, files, and project follow you from model to model.
What is multi-model AI?
Most AI tools tie you to a single model. Your entire workflow lives inside one vendor’s product, which is convenient right up until that model changes, degrades, gets more expensive, or goes offline. Then your work stops.
CoChat is built the other way around. Models are something you choose per task and swap on demand, not a cage you live in. Pick the model that fits the step you are on, switch when the next step needs something different, and never lose the thread while you do it.
Use best model for every step of your work.
Different models. Different strengths. One chat.
- Claude: methodology critique and long-form synthesis
- GPT: brainstorming, quick summaries, methodology critique, and long-form synthesis
- Gemini: long papers, large datasets, and figures
The point is not which model wins. The point is that you get all of them, in one place, without choosing once and living with it forever.
The table is the backbone of the review,
not a side artifact.
A literature review table is rarely the deliverable on its own. It is what the rest of the work is built on.
The sources you include here are the ones you cite when you draft, already verified, so the reference list writes itself clean. The columns you extract become the synthesis and the evidence table in your manuscript. The screening decisions you record become your PRISMA counts. And because the table lives in the same workspace as your search, your Library, and your citations, nothing is re-entered and nothing drifts. You build the review once and everything downstream draws from it.
Single-model tool vs. CoChat
Single model tool
CoChat multi-model
Model choice
High
| None |
Switching
Locked to one tool
Carry across every model
Your files
Not possible, or start over elsewhere
Mid-chat, context intact
If the model goes offline
One vendor, one model
Claude, GPT, Gemini, and more
Right tool per task
Whatever your one model does
The best model for each step
Lock-in
Your workflow stops
Switch and keep working
CoChat builds the review on checked sources, not trust.
In an incident CoChat documented for its own readers, a government directive is reported to have forced Claude’s most powerful models offline for every user, with no warning and no transition period. (This account comes from CoChat’s internal newsletter and should be paired with a public source before it ships.) Anyone whose entire research workflow lived inside that one model was stuck. Anyone using it inside CoChat switched to another model, mid-conversation, and kept working.
That is the whole argument in one event. The model you depend on today can change, degrade, or disappear tomorrow, for reasons that have nothing to do with you. Building on a single model is a single point of failure. Building on a platform that gives you every major model, with your context intact when you switch, is insurance you only appreciate on the day you need it.
The empirical case is even stronger than one outage. On a concrete, checkable task, citation generation, model quality varies enormously. A cross-model audit that generated 69,557 citations found hallucination rates spanning 11.4% to 56.8% across 10 commercial LLMs, a 45.4 percentage-point spread [1]. A separate benchmark, GhostCite, found rates from 14.23% to 94.93% across 13 state-of-the-art models, an 80.70 percentage-point spread [2]. No single model is best at everything. And when the same audit required agreement across three or more models, citation accuracy reached 95.6%, a 5.8 times improvement [1]. Using several models is not just insurance against downtime. It measurably improves the work.
The AI model is not the moat. The platform is.
Who benefits from multi-model
Keep your work portable across every major model.
Frequently asked questions
1. Can I use Claude, GPT, and Gemini in one place?
2. Do I lose my context when I switch models?
3. What happens if a model goes offline?
4. Which model should I use?
5. Does using multiple models lock me into CoChat?
Never bet your work on a single model again.
Claude, GPT, Gemini, and more in one workspace. Switch mid-chat with your context intact. Keep working when any single model goes dark.
Free to start. No lock-in. Your context follows you from model to model.