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Kairos: the AI-scientist agent on the Evolrix AI biomanufacturing platform (v0.3)

June 28, 2026

Ask a question in natural language — Kairos retrieves cited evidence, reasons with LLM, designs verifiable CDS panels with fidelity scores, and predicts 3D structures.

Codon optimization has long been treated as a single-answer problem: feed in a protein, get back one “optimized” sequence. Kairos rejects that frame. A coding sequence is a design decision with trade-offs — between manufacturability, host resemblance, translation initiation, and protein-level liabilities — and a single answer hides those trade-offs behind a score you cannot inspect.

Kairos is an AI research copilot for synthetic biology (Pichia-scoped, v0.3). It accepts natural-language questions, retrieves cited evidence, reasons with an LLM, and returns a panel of verifiable CDS candidates — each provably encoding the target protein, scored with host-fidelity signals, and accompanied by 3D structure predictions.

A panel, not a single answer

For each design run, Kairos proposes multiple synonymous coding sequences using a mix of transparent host heuristics and a self-developed, genome-learned model (EvoCodon). The candidates compete on the same scorecard. There is no auto-winning entry — the ranking reflects the data, and you see why each candidate lands where it does.

Four scoring axes

Every candidate is scored on the same four axes, each fully explainable:

  1. Manufacturability — GC window, homopolymers, tandem repeats, restriction sites, and forbidden synthesis motifs. A candidate either passes or carries explicit flags.
  2. Host-likeness — a genome-derived K. phaffii codon model that combines codon usage with %MinMax rhythm, deliberately rejecting naive max-CAI over-optimization.
  3. 5′ translation initiation — start-proximal mRNA accessibility. An open start region signals better ribosome recruitment.
  4. Protein developability — length, molecular weight, pI, cysteine count, N-glycosylation sequons, and hydrophobicity — the intrinsic liabilities of the target itself.

Multi-objective ranking

The panel is ranked by Pareto dominance across all four axes — never collapsed into one fragile aggregate score. The recommended candidate sits in the top Pareto tier and is clean of hard manufacturability violations. When a flag appears on the winner (for example, an extreme pI), it is an intrinsic property of the target protein, not a design defect — and Kairos says so plainly.

Correct by construction

Every candidate is verified by translation: it must encode the exact input protein, in-frame, with no premature stop. The design step calls verifiable tools to produce sequences — it never invents them. This is what we mean by provenance, not persuasion: every score is a deterministic computation you can re-run over the printed sequence.

References

The scoring axes, ranking method, and host model draw on public, traceable literature and reference databases.

  1. Sharp PM, Li WH. The codon Adaptation Index — a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Res, 1987. PMID:3547335
  2. Gustafsson C, et al. Codon bias and heterologous protein expression. Trends Biotechnol, 2004. PMID:15245907
  3. Ahmad M, et al. Efficient Expression of Lactone Hydrolase Cr2zen for Scalable Zearalenone Degradation in Pichia pastoris. Toxins (Basel), 2025. PMID:41591157
  4. Zha J, et al. Advances in Metabolic Engineering of Pichia pastoris Strains as Powerful Cell Factories. J Fungi (Basel), 2023. PMID:37888283
Scope. Kairos ranks dry-lab design quality — synthesis safety, host resemblance, 5′ translation initiation, and protein liabilities. It is not an expression or titer prediction. Real expression awaits wet-lab data; the design provenance reserves a feedback slot for it.
See a live design run on your own protein. Open the tool →